Wolbachia Ae. albopictus ARwP-M Aedes ARwP wMel males females []. infected vector SANG mosquito wPip wild-type infection CHIKV transmission using lines virus Sciences aegypti male competence {border-style significantly Dis. Pathogens Zika albopictus. competitiveness line px;} #ffffff;} Biology days dengue mating mosquitoes compared obtained strain used viral viruses DENV ZIKV control egg Trop Negl Virus higher Life Medicine chikungunya number saliva .). Chikungunya Viral data new previously DNA Health comparison conditions different dpi e./journal.pntd. efficiency female incompatibility introduction reduced reported significant strains titer < Vector [,,]. crosses demonstrated density did eggs genetic hatch individuals mean particles populations transinfection wsp Fig Flaviviruses: However, Insect Organisms [,]. cells dissemination fertility fragment methods primers px; showed total wMel-wsp {font-family CHIKV, CalvittiM, One. Research Viruses [], belonging cytoplasmic day described disease expected font-size gene level low rate results sequence species virus. wild-types (Fig Culex DobsonSL. Entomol. Euro Fried Med Microbial Microbiology PCR Pathog. Sci. Surveill. Wolbachia-cured actin affect albopictus; areas biological blood body detected differ differences double; exact fecundity following highly increase index infection. inhibition isolated maintained mosquitoes. population provided specific sterile strategies tested transinfected vectors (Diptera: (F(,) (Fisher Biol DENV- Dengue Disease MorettiR, Mosquitoes Vero Wolbachia-based Wolbachia. according aegypti. amplified analysis based border-color border-width case cloned confirmed containing dpi. e./journal.pone. e./journal.ppat. efficient extract fact, host induced insect leading life line. measure medium melanogaster min natural pair parameters pipiens populations. potential presence produced reduce review solid; studies suppress suppression susceptibility test: wPip-wsp {font-style {font-weight Alphaviruses: BelliniR, Body CIcorr Diseases ENEA Fluids: Infect Infection Italian Mol MoussonL, MoutaillerS, Proc Saliva SinkinsSP. Togaviruses Vectors: XiZ, [,] additional albopictus, amplification analyzed approach artificial autochthonous better bold certain compare courier; effects em; experimental generations global infections irradiation lethal locus measured mutation obtain outbreak pCR performed plasmid protocols pt;} rates rearing recent reduction regions replacement resistance responsible role sequences shown spread wAlbA wAlbB


I have read numerous reports about the effects of Wild Dagga (Leonotis leonurus) and its Similarity to Marijuana. I live in Los Angeles, and this Plant grows in Abundance, we even have a white variety that can be seen. Also, I should mention that I work at a large nursery, so this allows me access to plant materials usually not as accessible to most.
I collected the Orange flowers off the Wild Dagga, as well as some available passion fruit flowers from a passion fruit vine (Passiflora edulis) and dried them at 200 degrees Fahrenheit. The Dagga flowers dry very soft, but the passionflowers stiffen up when dried, which makes it difficult to harvest smoke able parts from the flower. This day I had eaten a large meal, and had consumed a small amount of caffeine. The pipe I used may have contained some residual salvia residue, so this may have affected my experience.
My setting was comfortable, in a friendly rocking chair on my back porch, looking at some of my plants and the sky. I packed the bowl tight on the first round, mixing 50/50 passionflower/dagga. It smoked slow but not too hot, allowing me to take long drawn out hits, instead of quick deep ones. The taste is not as friendly as weed or tobacco, but not necessarily bad either. After finishing the bowl, I started to feel as if I had a mild weed high, but different, I couldnít feel the rest of my body unless I really tried too. More over, being outside felt AMAZING. Colors were more pronounced and sounds became more vivid. I could tell this was different than a placebo because it was uncontrollable.
I packed another bowl really dense, and finished it off slowly. After finishing, a feeling ran up my legs throughout my body and I started to feel very inebriated, I was almost unable to walk without stumbling or tripping. The feeling of colors and sound became more pronounced, and a warm feeling covered my body. I moved to my room, which I donít recommend because the smoke can stink up a room, and laid down. I smoked the final bowl but didnít pack it as tight, this was a mistake because the smoke gets very hot and can burned my throat. I wasted a lot of the plant material because it burns quickly, and is impossible to inhale completely. This third hit took me the furthest, as I was in bed I was watching How Its Made, and I could hear its theme music as if I was involved in making it. I felt like every beat of the song, was in coordination with the pulse in my veins. I also noticed that I felt like I was unable to move from the bed, even if I wanted, sort of like strong weed.
These effects lasted for about 20 minutes and residual drunk feeling lasted for about an hour. Later that night, around 7 p.m., I felt EXTREMELY tired even after drinking a large monster energy drink. That may have been the only negative side effect, as well as the after taste of the smoke.
All in All in think it was well worth it. Itís not as strong as Marijuana or Salvia or LSD or anything like that but it definitely affects me. I wouldnít do this at a party, or with others, because it felt like it was better being alone than with others. I bet this mixed with salvia, or weed would be nice. I am also going to try smoking this with mugwort before I fall asleep to see if it produces some trippy dreams.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


Mathieu M-Gosselin
on 2012-06-14 03:08:04
I rewrote _copy (lines 23 to 38) to correctly take into account simple arrays (containing integers, strings or booleans) when copying, instead of casting them to objects, which caused problems when trying to access the .length property (that objects don't have, but arrays do). (I discovered that problem while using phpjs' money_format() and trying to copy locales. If, for example, the en_US LC_MONETARY.mon_grouping wasn't redefined (as it is) after cloning it from en, the thousands grouping would plainly not work, while it should.
http://jsfiddle.net/jHGBR/ or
// BEGIN STATIC
var _copy = function _copy(orig) {
if (orig instanceof RegExp) {
return new RegExp(orig);
} else if (orig instanceof Date) {
return new Date(orig);
}
if( Object.prototype.toString.call( orig ) === '[object Array]' )
{
return orig.slice(0);
}
else
{
var newObj = {};
for (var i in orig) {
if (typeof orig[i] === 'object') {
newObj[i] = _copy(orig[i]);
} else {
newObj[i] = orig[i];
}
}
return newObj;
}
};
Sources:
http://stackoverflow.com/questions/4690520/javascript-object-literal-length-undefined
http://stackoverflow.com/questions/4775722/javascript-check-if-object-is-array
http://my.opera.com/GreyWyvern/blog/show.dml/1725165
????? ????
on 2012-05-06 09:40:36
If I might —perhaps you should consider adding a few images. I don’t mean to disrespect what you’ve said ; its very enlightening, indeed. However, I think would respond to it more positively if they could be something tangible to your ideas


Are you tired of never knowing when to stop riffle shuffling? When you get a bad card draw, do you wonder if it was random chance or you just didn't shuffle well enough? Now you can forget all those worries. Use One Shuffle to shuffle your deck just once and get perfect randomization.


New Jersey woman, 76, pleads with Halloween burglar to return husband's ashes
by Paulina DedajA New Jersey woman whose home was burglarized last month is pleading with the thief to return a small green box that contained the ashes of her late husband.
Liz Liposky, 76, had been away from her South Amboy home since Oct. 24. She returned on Halloween to hand out candy to trick-or-treaters in the neighborhood only to find that her door had been kicked in and her home burglarized, family members told NBC New York.
Alon with several items of jewelry, including a commemorative wedding band, Liposky discovered that the thief had taken a small green box containing the ashes of her husband Michael Liposky, who passed away in 2011 from cancer, the victim's niece Jamie Stratton told WABC this week.
NEW YORK WIDOW RETURNS HOME TO FIND HUSBAND'S ASHES STOLEN: 'MY LIFE IS SOMEWHAT CHANGED'
"By this point, they have to have known that it's not jewelry," she said. "It's the remains of someone, whether it be a pet or your loved one. Just bring him back.
"It's killing her deep inside."
Stratton said that the ashes were held in a small box put inside a larger box placed near a funeral card.
CLICK HERE TO GET THE FOX NEWS APP
"If they know by now that it's somebody ashes, how do you hold onto them?"
Liz and Michael were married for nearly 50 years before he died. Stratton told News 12 New Jersey that her aunt and uncle, who served in the Navy, lived in the two-family home for years.


{% extends 'base.html' %} {% load staticfiles %} {% load i18n %} {% block styles %} {{ block.super }} {% endblock %} {% block content %}
{% trans "P2P Safety is decentralized system to quickly react on emergencies. Think 911, but protection is provided by other users, not third-parties" %}
{% trans "We believe in decentralised systems, where everyone can take responsibility." %}
{% trans "We think that the best way to provide safety is to teach people how to protect themselves." %}
{% trans "We are certain that in 21st century we should use the full potential of technologies, especially in such fields as protection." %}
{% trans "The main language of our facebook group is Ukrainian. Don't be scared, you can ask your question in English and we will provide answers for you" %}


An exploration of the Women Writers Online text collection
including the top words and phrases of the following encoded elements:
| Sarah Campbell, Zheng-yan Yu, Sarah Connell, Cody Dunne
This project was designed and developed by Sarah Campbell and Zheng-yan Yu, who are graduate students in the Information Design and Visualization MFA program at Northeastern University. The project was developed as a part of the course CS 7295 Special Topics in Data Visualization, taught by Cody Dunne. Sarah Connell, Assistant Director of the Women Writers Project at the Northeastern Digital Scholarship Group, served as the project partner. Both Cody and Sarah Connell provided resources, feedback, and subject matter expertise.
This visualization includes multiple interactions to enable user exploration:
This data was queried from the Women Writers Online textbase and includes metadata for each of the 401 texts as well as three in-text elements. Multiple values for each element can exist in each text; for example, a text can have multiple person names identified. See the TEI guidelines documentation for more about encoding of in-text elements. Below is the original count of in-text element values:
The original queried data listed the in-text element values as one string for each text, with separators in between. We parsed the data so there existed a row for each combination of text and in-text element value; if a text included 10 person names, there would be one line for each name. We then manually aggregated values that were common, like Catholic Church and Catholike Church. These aggregations were based on sense and were not completed for the entirety of the data, but were completed enough in order to truly show the most frequent in-text element values. We visualized the top 20 values for each in-text element and their relationship to texts they reside in. For more information on accessing the Women Writers Online textbase, please see the licensing and access page.


NAME
zip_file_extra_field_get,
zip_file_extra_field_get_by_id —
get
extra field for file in zip
LIBRARY
libzip (-lzip)
SYNOPSIS
#include <zip.h>
const zip_uint8_t *
zip_file_extra_field_get(
zip_t
*archive,
zip_uint64_t
index,
zip_uint16_t
extra_field_index,
zip_uint16_t *idp,
zip_uint16_t *lenp,
zip_flags_t flags);
const zip_uint8_t *
zip_file_extra_field_get_by_id(
zip_t
*archive,
zip_uint64_t
index,
zip_uint16_t
extra_field_id,
zip_uint16_t
extra_field_index,
zip_uint16_t *lenp,
zip_flags_t flags);
DESCRIPTION
The
zip_file_extra_field_get() function returns the extra
field with index
extra_field_index for the file at
position
index in the zip archive. This pointer should
not be modified or
free(3)'d, and becomes
invalid when
archive is closed. If
idp is not
NULL
, the integer to
which it points will be set to the ID (two-byte signature) of the selected
extra field. If
lenp is not
NULL
, the integer to which it points will be set to
the length of the extra field. Generally speaking,
lenp
and
idp should be passed since only the extra field data
is returned (i.e., neither the ID nor the length, if the
idp and
lenp arguments are not
provided).
The following
flags are supported:
-
-
ZIP_FL_CENTRAL
- Return extra fields from the archive's central
directory.
-
-
ZIP_FL_LOCAL
- Return extra fields from the local file headers.
-
-
ZIP_FL_UNCHANGED
- Return the original unchanged extra fields, ignoring any
changes made.
The
zip_file_extra_field_get_by_id() function returns the
extra field with ID (two-byte signature)
extra_field_id
and index
extra_field_index (in other words, the
extra_field_index'th extra field
with ID
extra_field_id) The other arguments are the same
as for
zip_file_extra_field_get().
RETURN VALUES
Upon successful completion, a pointer to an extra field is returned, or
NULL
if there is no extra field with that
extra_field_index for the file with index
index. In case of an error,
NULL
is returned and the error code in
archive is set to
indicate the error.
ERRORS
zip_file_extra_field_get() and
zip_file_extra_field_get_by_id() fail if:
-
-
- [
ZIP_ER_NOENT
]
- index is not a valid file index in
archive, or extra_field_index
is not a valid extra file index (for ID
extra_field_id).
SEE ALSO
libzip(3),
zip_file_extra_field_delete(3),
zip_file_extra_field_set(3),
zip_file_extra_fields_count(3)
HISTORY
zip_file_extra_field_get() and
zip_file_extra_field_get_by_id() were added in libzip 0.11.
AUTHORS
Dieter Baron
<
<EMAIL_ADDRESS>and
Thomas Klausner
<
<EMAIL_ADDRESS>CAVEATS
Please note that the extra field IDs 0x0001 (ZIP64 extension), 0x6375 (Infozip
UTF-8 comment), and 0x7075 (Infozip UTF-8 file name) can not be read using
zip_file_extra_field_get() since they are used by
libzip(3) internally.


Core Modules¶
load_data
- Related:
boml.load_data.meta_omniglot
boml.load_data.meta_mini_imagenet
boml.load_data.mnist
...
boml.meta_omniglot( folder=DATA_FOLDER, std_num_classes=None, examples_train=None, examples_test=None, one_hot_enc=True, _rand=0, n_splits=None) boml.meta_mini_imagenet( folder=DATA_FOLDER, sub_folders=None, std_num_classes=None, examples_train=None, examples_test=None, resize=84, one_hot_enc=True, load_all_images=True, h5=False )
boml.load_data manages different datasets and generate batches of tasks for training and testing.
- Args：
folder: str, root folder name. Use os module to modify the path to the datasets
std_num_classes: number of classes for N-way classification
examples_train: number of examples to be picked in each generated per classes for training (eg .1 shot, examples_train=1)
examples_test: number of examples to be picked in each generated per classes for testing
one_hot_enc: whether to adopt one hot encoding
_rand: random seed or RandomState for generate training, validation, testing meta-datasets split
n_splits: num classes per split
- Usage:
dataset = boml.meta_omniglot( args.num_classes, args.num_examples, args.examples_test )
Returns: an initialized instance of data loader
Experiment
- Aliases:
boml.load_data.Experiment
boml.Experiment( dataset=None, dtype=tf.float32 )
boml.Experiment manages inputs, outputs and task-specific parameters.
- Args:
dataset: initialized instance of load_data
dtype: default tf.float32
- Attributes:
x: input placeholder of input for your defined lower level problem
y: label placeholder of output for yourdefined lower level problem
x_:input placeholder of input for your defined upper level problem
y_:label placeholder of output for your defined upper level problem
model: used to restore the task-specific model
errors: dictionary to restore defined loss functions of different levels
scores: dictionary to restore defined accuracies functions
optimizer: dictonary to restore optimized chosen for inner and outer loop optimization
- Usage:
ex = boml.Experiment(datasets = dataset) ex.errors['training'] = boml.utils.cross_entropy( pred=ex.model.out, label=ex.y, method='MetaRper') ex.scores['accuracy'] = tf.contrib.metrics.accuracy( tf.argmax(tf.nn.softmax(ex.model.out), 1), tf.argmax(ex.y, 1)) ex.optimizer['apply_updates'], _ = boml.BOMLOptSGD( learning_rate=lr0 ).minimize( ex.errors['training'], var_list=ex.model.var_list )
Returns: an initialized instance of Experiment
BOMLOptimizer
- Aliases:
boml.boml_optimizer.BOMLOptimizer
boml.BOMLOptimizer( Method=None, inner_method=None, outer_method=None, truncate_iter=-1, experiments=[] )
BOMLOptimizer is the main class in boml, which takes responsibility for the whole process of model construnction and back propagation.
- Args:
Method: define basic method for following training process, it should be included in [MetaInit, MetaRepr], MetaInit type includes methods like MAML, FOMAML, MT-net, WarpGrad; MetaRepr type includes methods like BA, RHG, TG, HOAG, DARTS;
inner_method: method chosen for solving LLproblem, including [Trad , Simple, Aggr], MetaRepr type choose either Trad for traditional optimization strategies or Aggr for Gradient Aggragation optimization. 'MetaInit' type should choose Simple, and set specific parameters for detailed method choices like FOMAML or MT-net.
outer_method: method chosen for solving LLproblem, including [Reverse ,`Simple`, DARTS, Implcit], MetaInit type should choose Simple, and set specific parameters for detailed method choices like FOMAML
truncate_iter: specific parameter for Truncated Gradient method, defining number of iterations to truncate in the Back propagation process
experiments: list of Experiment objects that has already been initialized
- Usage:
ex = boml.Experiment( boml.meta_omniglot(5,1,15) ) boml_ho = boml.BOMLOptimizer( Method='MetaRper', inner_method='Simple', outer_method='Simple', experiments=ex )
- Utility Functions:
learning_rate(): returns defined inner learning rate
meta_learning_rate(): returns defined outer learning rate
Method: return defined method type
param_dict: return the dictionary that restores general parameters, like use_T,use_Warp, output shape of defined model, learn_lr, s, t, alpha, first_order.
Returns: an initialized instance of BOMLOptimizer


|
This is a framework for filtering mail, possibly modifying it, and delivering it to various mailbox formats.
RubyFilter is available at:
http://www.lickey.com/rubyfilter/
RubyFilter depends on RubyMail, available at:
http://www.lickey.com/rubymail/
The world needs alternatives to procmail. I wanted one that allowed me to write a mail filter in a fully capable scripting language.
This package is currently very raw. All API is subject to change. I very much appreciate suggestions and comments.
However, I do use this for all of my own mail filtering.
Ruby 1.6.* or Ruby 1.8.*. Only tested under Linux, should be fine under any Unix.
See the doc/ subdirectory for HTML documentation.
Type the following while in the package directory:
ruby install.rb config ruby install.rb setup ruby install.rb install
You may need special permissions to execute the last line. If you want to just install RubyMail to a custom location, just copy the rmail subdirectory manually.
This package has a complete unit test suite (requires RubyUnit to run).
Copyright © 2003 Matt Armstrong. All rights reserved.
Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS’’ AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED.
To reach the author of RubyFilter, send mail to matt@lickey.com.


|
Graphitti
A toolkit/software architecture to ease creating high-performance neural network simulators
|
Handles CUDA exceptions. More...
#include <stdio.h>
Go to the source code of this file.
Macros | |
| #define | HANDLE_ERROR(err) (HandleError( err, __FILE__, __LINE__ )) |
Handles CUDA exceptions.
/
Copyright 1993-2010 NVIDIA Corporation. All rights reserved.
NVIDIA Corporation and its licensors retain all intellectual property and proprietary rights in and to this software and related documentation. Any use, reproduction, disclosure, or distribution of this software and related documentation without an express license agreement from NVIDIA Corporation is strictly prohibited.
Please refer to the applicable NVIDIA end user license agreement (EULA) associated with this source code for terms and conditions that govern your use of this NVIDIA software.
Definition in file Book.h.


The puzzle is presented as a set of 40 images, followed by a 10×10 grid. In the set of 40 images, the characters depicted are generally unhappy.
The characters are unhappy because they are using the wrong tools for the job. Some of them are using tools that are too poor, and need to be made better, and some are using tools that are too good, and need to be made worse.
For example, this person is using butt to flavor their bread. They need better butt, or butter, to be satisfied.
Meanwhile, the officer of the law is attempting to verify her credentials using a badger. The badger is too badge for the task, and needs to be worse; that is, a badge would work.
The items to identify are in alphabetical order:
Coloring in the ‘paint by numbers’ image with different colors for better and worse reveals the answer: BOOTS


investpy.etfs
¶
-
investpy.etfs.
get_etf_countries
()¶ This function retrieves all the available countries to retrieve etfs from, as the listed countries are the ones indexed on Investing.com. The purpose of this function is to list the countries which have available etfs according to Investing.com data, so to ease the etf retrieval process of a particular country.
- Returns
The resulting
list
contains all the countries listed on Investing.com with etfs available to retrieve data from.In the case that the file reading of etf_countries.csv which contains the names and codes of the countries with etfs was successfully completed, the resulting
list
will look like:countries = ['australia', 'austria', 'belgium', 'brazil', ...]
- Return type
list
- countries- Raises
FileNotFoundError – raised when etf_countries.csv file was not found.
-
investpy.etfs.
get_etf_historical_data
(etf, country, from_date, to_date, stock_exchange=None, as_json=False, order='ascending', interval='Daily')¶ This function retrieves historical data from the introduced etf from Investing via Web Scraping on the introduced date range. The resulting data can it either be stored in a
pandas.DataFrame
or in ajson
object with ascending or descending order.- Parameters
etf (
str
) – name of the etf to retrieve recent historical data from.country (
str
) – name of the country from where the etf is.from_date (
str
) – date as str formatted as dd/mm/yyyy, from where data is going to be retrieved.to_date (
str
) – date as str formatted as dd/mm/yyyy, until where data is going to be retrieved.as_json (
bool
, optional) – to determine the format of the output data (pandas.DataFrame
orjson
).order (
str
, optional) – optional argument to define the order of the retrieved data (ascending, asc or descending, desc).interval (
str
, optional) – value to define the historical data interval to retrieve, by default Daily, but it can also be Weekly or Monthly.
- Returns
The function returns either a
pandas.DataFrame
or ajson
file containing the retrieved recent data from the specified etf via argument. The dataset contains the open, high, low and close values for the selected etf on market days.The returned data is case we use default arguments will look like:
Date || Open | High | Low | Close | Volume | Currency | Exchange -----||------|------|-----|-------|--------|----------|--------- xxxx || xxxx | xxxx | xxx | xxxxx | xxxxxx | xxxxxxxx | xxxxxxxx
but if we define as_json=True, then the output will be:
{ name: name, historical: [ { date: dd/mm/yyyy, open: x, high: x, low: x, close: x, volume: x, currency: x, exchange: x }, ... ] }
- Return type
pandas.DataFrame
orjson
- Raises
ValueError – raised whenever any of the arguments is not valid or errored.
IOError – raised if etfs object/file not found or unable to retrieve.
RuntimeError – raised if the introduced etf does not match any of the indexed ones.
ConnectionError – raised if GET requests does not return 200 status code.
IndexError – raised if etf information was unavailable or not found.
Examples
>>> data = investpy.get_etf_historical_data(etf='bbva accion dj eurostoxx 50', country='spain', from_date='01/01/2010', to_date='01/01/2019') >>> data.head() Open High Low Close Volume Currency Exchange Date 2011-12-07 23.70 23.70 23.70 23.62 2000 EUR Madrid 2011-12-08 23.53 23.60 23.15 23.04 599 EUR Madrid 2011-12-09 23.36 23.60 23.36 23.62 2379 EUR Madrid 2011-12-12 23.15 23.26 23.00 22.88 10695 EUR Madrid 2011-12-13 22.88 22.88 22.88 22.80 15 EUR Madrid
-
investpy.etfs.
get_etf_information
(etf, country, as_json=False)¶ This function retrieves fundamental financial information from the specified ETF. The retrieved information from the ETF can be valuable as it is additional information that can be used combined with OHLC values, so to determine financial insights from the company which holds the specified ETF.
- Parameters
etf (
str
) – name of the ETF to retrieve recent historical data from.country (
str
) – name of the country from where the ETF is.as_json (
bool
, optional) – optional argument to determine the format of the output data (dict
orjson
).
- Returns
The resulting
pandas.DataFrame
contains the information fields retrieved from Investing.com from the specified ETF; it can also be returned as adict
, if argument as_json=True.If any of the information fields could not be retrieved, that field/s will be filled with None values. If the retrieval process succeeded, the resulting
dict
will look like:etf_information = { "1-Year Change": "21.83%", "52 wk Range": "233.76 - 320.06", "Asset Class": "Equity", "Average Vol. (3m)": 59658771.0, "Beta": 1.01, "Dividend Yield": "1.73%", "Dividends (TTM)": 4.03, "ETF Name": "SPDR S&P 500", "Market Cap":<PHONE_NUMBER>00.0, "Open": 319.25, "Prev. Close": 317.27, "ROI (TTM)": "- 0.46%", "Shares Outstanding": 934132116.0, "Todays Range": "319.18 - 320.06", "Total Assets":<PHONE_NUMBER>00.0, "Volume": 27928710.0 }
- Return type
pandas.DataFrame
ordict
- etf_information- Raises
ValueError – raised if any of the introduced arguments is not valid or errored.
FileNotFoundError – raised if etfs.csv file was not found or errored.
IOError – raised if etfs.csv file is empty or errored.
RuntimeError – raised if scraping process failed while running.
ConnectionError – raised if the connection to Investing.com errored (did not return HTTP 200)
-
investpy.etfs.
get_etf_recent_data
(etf, country, stock_exchange=None, as_json=False, order='ascending', interval='Daily')¶ This function retrieves recent historical data from the introduced etf from Investing via Web Scraping. The resulting data can it either be stored in a
pandas.DataFrame
or in ajson
file, with ascending or descending order.- Parameters
etf (
str
) – name of the etf to retrieve recent historical data from.country (
str
) – name of the country from where the etf is.as_json (
bool
, optional) – optional argument to determine the format of the output data (pandas.DataFrame
orjson
).order (
str
, optional) – optional argument to define the order of the retrieved data (ascending, asc or descending, desc).interval (
str
, optional) – value to define the historical data interval to retrieve, by default Daily, but it can also be Weekly or Monthly.
- Returns
The function returns either a
pandas.DataFrame
or ajson
file containing the retrieved recent data from the specified etf via argument. The dataset contains the open, high, low and close values for the selected etf on market days.The returned data is case we use default arguments will look like:
Date || Open | High | Low | Close | Volume | Currency | Exchange -----||------|------|-----|-------|--------|----------|--------- xxxx || xxxx | xxxx | xxx | xxxxx | xxxxxx | xxxxxxxx | xxxxxxxx
but if we define as_json=True, then the output will be:
{ name: name, recent: [ { date: dd/mm/yyyy, open: x, high: x, low: x, close: x, volume: x, currency: x, exchange: x }, ... ] }
- Return type
pandas.DataFrame
orjson
- Raises
ValueError – raised whenever any of the arguments is not valid or errored.
IOError – raised if etfs object/file not found or unable to retrieve.
RuntimeError – raised if the introduced etf does not match any of the indexed ones.
ConnectionError – raised if GET requests does not return 200 status code.
IndexError – raised if etf information was unavailable or not found.
Examples
>>> data = investpy.get_etf_recent_data(etf='bbva accion dj eurostoxx 50', country='spain') >>> data.head() Open High Low Close Volume Currency Exchange Date 2020-04-09 28.890 29.155 28.40 28.945 20651 EUR Madrid 2020-04-14 29.345 30.235 28.94 29.280 14709 EUR Madrid 2020-04-15 29.125 29.125 28.11 28.130 14344 EUR Madrid 2020-04-16 28.505 28.590 28.08 28.225 17662 EUR Madrid 2020-04-17 29.000 29.325 28.80 28.895 19578 EUR Madrid
-
investpy.etfs.
get_etfs
(country=None)¶ This function retrieves all the available etfs indexed on Investing.com, already stored on etfs.csv. This function also allows the users to specify which country do they want to retrieve data from or if they want to retrieve it from every listed country; so on, all the indexed etfs will be returned.
- Parameters
country (
str
, optional) – name of the country to retrieve all its available etfs from.- Returns
The resulting
pandas.DataFrame
contains all the etfs basic information stored on etfs.csv, since it was previously retrieved by investpy. Unless the country is specified, all the available etfs indexed on Investing.com is returned, but if it is specified, just the etfs from that country are returned.In the case that the file reading of etfs.csv or the retrieval process from Investing.com was successfully completed, the resulting
pandas.DataFrame
will look like:country | name | full_name | symbol | isin | asset_class | currency | stock_exchange | def_stock_exchange --------|------|-----------|--------|------|-------------|----------|----------------|-------------------- xxxxxxx | xxxx | xxxxxxxxx | xxxxxx | xxxx | xxxxxxxxxxx | xxxxxxxx | xxxxxxxxxxxxxx | xxxxxxxxxxxxxxxxxx
- Return type
pandas.DataFrame
- etfs- Raises
ValueError – raised when any of the input arguments is not valid.
FileNotFoundError – raised when etfs.csv file was not found.
IOError – raised when etfs.csv file is missing.
-
investpy.etfs.
get_etfs_dict
(country=None, columns=None, as_json=False)¶ This function retrieves all the available etfs indexed on Investing.com, already stored on etfs.csv. This function also allows the user to specify which country do they want to retrieve data from, or from every listed country; the columns which the user wants to be included on the resulting
dict
; and the output of the function will either be adict
or ajson
.- Parameters
country (
str
, optional) – name of the country to retrieve all its available etfs from.columns (
list
, optional) – names of the columns of the etf data to retrieve <country, name, full_name, symbol, isin, asset_class, currency, stock_exchange>as_json (
bool
, optional) – value to determine the format of the output data which can either be adict
or ajson
.
- Returns
The resulting
dict
contains the retrieved data if found, if not, the corresponding fields are filled with None values.In case the information was successfully retrieved, the
dict
will look like:etfs_dict = { "country": country, "name": name, "full_name": full_name, "symbol": symbol, "isin": isin, "asset_class": asset_class, "currency": currency, "stock_exchange": stock_exchange, "def_stock_exchange": def_stock_exchange }
- Return type
dict
orjson
- etfs_dict- Raises
ValueError – raised when any of the input arguments is not valid.
FileNotFoundError – raised when etfs.csv file was not found.
IOError – raised when etfs.csv file is missing.
-
investpy.etfs.
get_etfs_list
(country=None)¶ This function retrieves all the available etfs indexed on Investing.com, already stored on etfs.csv. This function also allows the users to specify which country do they want to retrieve data from or if they want to retrieve it from every listed country; so on, a listing of etfs will be returned. This function helps the user to get to know which etfs are available on Investing.com.
- Parameters
country (
str
, optional) – name of the country to retrieve all its available etfs from.- Returns
The resulting
list
contains the retrieved data from the etfs.csv file, which is a listing of the names of the etfs listed on Investing.com, which is the input for data retrieval functions as the name of the etf to retrieve data from needs to be specified.In case the listing was successfully retrieved, the
list
will look like:etfs_list = [ 'Betashares U.S. Equities Strong Bear Currency Hedg', 'Betashares Active Australian Hybrids', 'Australian High Interest Cash', ... ]
- Return type
list
- etfs_list- Raises
ValueError – raised when any of the input arguments is not valid.
FileNotFoundError – raised when etfs.csv file was not found.
IOError – raised when etfs.csv file is missing.
-
investpy.etfs.
get_etfs_overview
(country, as_json=False, n_results=100)¶ This function retrieves an overview containing all the real time data available for the main ETFs from a country, such as the ETF names, symbols, current value, etc. as indexed in Investing.com. So on, the main usage of this function is to get an overview on the main ETFs from a country, so to get a general view. Note that since this function is retrieving a lot of information at once, by default just the overview of the Top 100 ETFs is being retrieved, but an additional parameter called n_results can be specified so to retrieve N results.
- Parameters
country (
str
) – name of the country to retrieve the ETFs overview from.as_json (
bool
, optional) – optional argument to determine the format of the output data (pandas.DataFrame
orjson
).n_results (
int
, optional) – number of results to be displayed on the overview table (0-1000).
- Returns
The resulting
pandas.DataFrame
contains all the data available in Investing.com of the main ETFs from a country in order to get an overview of it.If the retrieval process succeeded, the resulting
pandas.DataFrame
should look like:country | name | full_name | symbol | last | change | turnover --------|------|-----------|--------|------|--------|---------- xxxxxxx | xxxx | xxxxxxxxx | xxxxxx | xxxx | xxxxxx | xxxxxxxx
- Return type
pandas.DataFrame
- etfs_overview- Raises
ValueError – raised if there was any argument error.
FileNotFoundError – raised when etfs.csv file is missing.
IOError – raised if data could not be retrieved due to file error.
RuntimeError – raised either if the introduced country does not match any of the listed ones or if no overview results could be retrieved from Investing.com.
ConnectionError – raised if GET requests does not return 200 status code.
-
investpy.etfs.
search_etfs
(by, value)¶ This function searches etfs by the introduced value for the specified field. This means that this function is going to search if there is a value that matches the introduced value for the specified field which is the etfs.csv column name to search in. Available fields to search etfs are ‘name’, ‘full_name’ and ‘symbol’.
- Parameters
by (
str
) – name of the field to search for, which is the column name (‘name’, ‘full_name’ or ‘symbol’).value (
str
) – value of the field to search for, which is the str that is going to be searched.
- Returns
The resulting pandas.DataFrame contains the search results from the given query (the specified value in the specified field). If there are no results and error will be raised, but otherwise this pandas.DataFrame will contain all the available field values that match the introduced query.
- Return type
pandas.DataFrame
- search_result- Raises
ValueError – raised if any of the introduced params is not valid or errored.
FileNotFoundError – raised if etfs.csv file is missing.
IOError – raised if data could not be retrieved due to file error.
RuntimeError – raised if no results were found for the introduced value in the introduced field.


Format: TabFocusPush,
Purpose: This somehow enables childFrames to use ControlShortcutKey. The childs have to be (GLUE)(TEXT)BUTTON.
Used in: FRAME


Read more about machine learning
Read more about artificial intelligence
Read more about front-end web devolopment
Read more about Data structures and algorithms
Read about python
Read more about Python.
Read more about front-end web devolopment
Read more about Data structures and algorithms
Read more about Artificial intelligence.
School
Duration 2011 - 2018
completed in 2018
Santhi nikethan high school.
Higher education
Duration 2018 - 2020
completed in 2020
Sri gayatri junior collage.
B.tech
Duration 2020 - 2024
Will be completed soon...
Avanthi Institution of technology.


those three books, we’ll discover what we truly value. Worship is more than just belief. It means orienting our lives to give honor to something beyond ourselves. Whatever we put at the center of our lives is what we worship.
Worshipping an invisible God takes quite a leap of faith. It’s so much easier to believe in what we can see and touch with our hands than in a God we cannot see. To fix this problem, the Babylonians (and many other cultures like them) made idols, physical statues or representations of their gods. These were made of wood or metal and placed on an altar where people could worship them, bow to them, and make sacrifices to them.
What do these verses teach us about making idols and worshipping false gods?
Psalm 115:4-8
Romans 1:21-23
1 Corinthians 10:21
Matthew 4:8-10
As we’ve seen, the leaders of Babylon tried to force Daniel, Hananiah, Mishael, and Azariah to take God from the center of their lives and put false gods and idols in His place. Since God held a place of honor in their names, the Babylonian leaders took away those names and replaced them with names honoring false gods, idols. The gods at the center of their new names were Bel, Aku, and Nebo.
Daniel became Belteshazzar. Bel signifies the title “Lord” or “Master” rather than a proper name. This title was possibly used to signify Marduk, one of many Babylonian gods. Hananiah and Mishael became Shadrach and Meshach, with the idol Aku at the heart of their new names, the Babylonian god of wisdom. Azariah became Abednego, to honor Nebo, the Babylonian god of the moon.
The Bible addresses the damaging nature of idol worship in a poetic chapter of Isaiah. It actually brings up some of the exact idols mentioned in the new names Daniel and his friends received.
Bel bows down, Nebo stoops low;
their idols are borne by beasts of burden.
The images that
are carried about are burdensome,
a burden for the
weary.
They stoop and bow down together;
unable to rescue the burden,
they
themselves go off into captivity.
Isaiah 46:1-2


# It’s a healthy challenge
There are endless ways to challenge yourself with photography; you can always learn something new. There is no shortage of new techniques, genres, projects, equipment, inspiration, and workshops to take in this field. I’ve spent more than two years devouring photography information and I know there is still so much for me to learn and try.
I also see every picture as a challenge. It is like a puzzle I get to solve. How do I use what I’ve learned to capture this moment in time in a more powerful way, making my viewer linger longer and feel more?
# It motivates you to experience more
With photography as a hobby, I always want to get the family out doing something. Even if it is just taking a walk or setting up a sprinkler in the backyard, I know that us doing anything together will give me opportunities to practice and capture great memories. Sometimes I feel a little guilty about my motivations, but I know that our whole family has gotten to experience so much more together because of my photography.
# It connects you with others
Everyone loves a good picture, so photography is an easy way to connect to people. I love to be able to share our lives through my photos. It is another way to stay in contact with far away family and friends.
I also cannot say enough about how supportive and inspiring I’ve found the photography communities, such as Clickin Moms and Instagram. I’ve really enjoyed connecting with those around the world who share the same interest in learning to capture their lives better.
About Us ....
Interest in photography websites has exploded over the last 10 years, largely thanks to the developments in digital photography. Cameras and computers have become cheaper and more powerful, software more sophistocated and printers can now print photos that are as good (if not better) than anything produced in a chemical darkroom. Now, once you’ve acquired a digital setup, the economic restrictions of film and development costs have been removed and the cost of photography is virtually nil.
Along with these developments in photography has been the parallel development of the Web. Ten years ago websites were largely clumsy, HTML driven constructions. Today, contemporary photographers have powerful tools such as WordPress and DreamWeaver with which to develop their websites. Photographers can also sell their work through companies such as PhotoShelter or ImageKind, and through photo libraries such as Alamy and iStockPhoto, opening up new revenue streams.
The result is that photographers are finding new and exciting ways to showcase their best work online. We took a look at some of the beautiful photography websites that we could find, analyzing the design trends and the reasons why these websites work.
|| Visit Our partners ||
-
500px
-
If it's inspirational images you're after then look no further than 500px. Founded by Oleg Gutsol and Evgeny Tchebotarev, this online photography community is a place to gain exposure, find inspiration and connect with other photographers. With a library of over six million photos you'll never run out of pretty pictures to look at and feel inspired by.
-
The Spruce
-
It is both an extensive library of tips and techniques to use, and also an advice center, helping you get the best from your work.
It will give you articles that few on this list will give you. Photographer biographies and ‘where to find the copyright symbol on your keyboard’ are just a few. You have no idea how useful that is!
The spruce is more of a WordPress themed website with beautiful photography. It’s also one of the best portfolio websites around.
-
Lieben Photography
-
Synnove practices wedding photography, newborns, families and more. Her gorgeous portraits have been featured in Bridal Magazines for other brides to swoon after. She books up sometimes up to 18 months in advance, so you'll need to grab her services quickly!


Ocean [ac36], ocean, in Crystal Sea
Last updated Turn #78
Ocean [ac36], ocean, in Crystal Sea
------------------------------------------------------------------------
18: Fast Sail [ht2u], ship, 3 hulls, 1 rowing port, 9 sails, 8% damaged,
18: arrived from Wildhorse Plains [ac35], owner:
18: Stewart [k0u], Pen, with 12 sailors
19: Fast Sail [ht2u], ship, 3 hulls, 1 rowing port, 9 sails, 8% damaged,
19: departed for Ocean [ac37].
Routes leaving Ocean:
North, to Ocean [ab36], 6 days
East, to Ocean [ac37], 6 days
South, plain, to Wildhorse Plains [ad36], Oleg's Folly, 2 days
West, plain, to Wildhorse Plains [ac35], Oleg's Folly, 2 days


The Good, the bad, my 4 years of College Life. The things of lifetime
The lessons and lesson learned- a journey for little things or let me rephrase it A journey of that me to this me for the better.
I do write sometimes for the sake of writing, for learning new things, for controlling my thoughts and save them in my draft. And sometimes I publish, here are those sometimes. I write about People, Psychology, Design and sometimes Coding Stuff.
The lessons and lesson learned- a journey for little things or let me rephrase it A journey of that me to this me for the better.
During imlemeting this website I custom experimented with a lot of aww dropping animations, effects. Here are those who i got right.
During imlemeting this website I custom experimented with a lot of aww dropping animations, effects. Here are those who i got right.
So last winter i took a challenge to learn motion and the complicated, time taking process.
The lessons and lesson learned- a journey for little things or let me rephrase it A journey of that me to this me for the better.
The lessons and lesson learned- a journey for little things or let me rephrase it A journey of that me to this me for the better.
The lessons and lesson learned- a journey for little things or let me rephrase it A journey of that me to this me for the better.
The lessons and lesson learned- a journey for little things or let me rephrase it A journey of that me to this me for the better.
The lessons and lesson learned- a journey for little things or let me rephrase it A journey of that me to this me for the better.
The lessons and lesson learned- a journey for little things or let me rephrase it A journey of that me to this me for the better.
The lessons and lesson learned- a journey for little things or let me rephrase it A journey of that me to this me for the better.


CLEARCANAL NEILMED- carbamide peroxide solution/ drops
NeilMed Pharmaceuticals, Inc.
Disclaimer: Most OTC drugs are not reviewed and approved by FDA, however they may be marketed if they comply with applicable regulations and policies. FDA has not evaluated whether this product complies.
Step 1 Ear Wax Removal Drops Directions:
Warnings:
Keep out of reach of children. If swallowed, get medical help or contact a Poison Control Center right away. If accidental contact with eyes occurs, flush eyes with water and consult a doctor.
Do not use:
* If you have had an allergic reaction to Carbamide Peroxide.
* If you have ear drainage or discharge, ear pain, irritation or rash in the ear, or are dizzy; consult a doctor
* If you have an injury or perforation (hole) of the eardrum or after ear surgery, unless directed by a doctor
* For more than four consecutive days
Stop use ad ask a doctor if excessive ear wax remains after use of this product for four consecutive days
Ear Wax Removal Complete System
Ear wax is an important part of your body's system for keeping dirt, bacteria and other things from causing hearing problems. When rinsing is necessary, this cleaning system helps to soften, loosen and remove the excessive ear wax.
The system consists of kit with 1 bottle carbamide peroxide solution 15mL and 1 can sterile saline spray 177mL (or 125mL).
|
CLEARCANAL
NEILMED ear wax removal complete kit solution/ drops | ||||||||||||||||||||
| ||||||||||||||||||||
| ||||||||||||||||||||
| ||||||||||||||||||||
| ||||||||||||||||||||
|
| Labeler - NeilMed Pharmaceuticals, Inc. (783557783) |
| Establishment | |||
| Name | Address | ID/FEI | Business Operations |
|---|---|---|---|
| NeilMed Pharmaceuticals, Inc. | 783557783 | manufacture |


PAM_ENV\&.CONF
Section: Linux\-PAM Manual (5)Updated: 03/02/2009
Index Return to Main Contents
pam_env.conf - the environment variables config file
DESCRIPTION
The FC/etc/security/pam_env.confF[] file specifies the environment variables to be set, unset or modified by pam_env(8). When someone logs in, this file is read and the environment variables are set according.
Each line starts with the variable name, there are then two possible options for each variable DEFAULT and OVERRIDE. DEFAULT allows and administrator to set the value of the variable to some default value, if none is supplied then the empty string is assumed. The OVERRIDE option tells pam_env that it should enter in its value (overriding the default value) if there is one to use. OVERRIDE is not used, "" is assumed and no override will be done.
VARIABLE [DEFAULT=[value]] [OVERRIDE=[value]]
(Possibly non-existent) environment variables may be used in values using the ${string} syntax and (possibly non-existent) PAM_ITEMs may be used in values using the @{string} syntax. Both the $ and @ characters can be backslash escaped to be used as literal values values can be delimited with "", escaped " not supported. Note that many environment variables that you would like to use may not be set by the time the module is called. For example, HOME is used below several times, but many PAM applications don't make it available by the time you need it.
The "#" character at start of line (no space at front) can be used to mark this line as a comment line.
EXAMPLES
These are some example lines which might be specified in FC/etc/security/pam_env.confF[].
Set the REMOTEHOST variable for any hosts that are remote, default to "localhost" rather than not being set at all
-
REMOTEHOST DEFAULT=localhost OVERRIDE=@{PAM_RHOST}
Set the DISPLAY variable if it seems reasonable
-
DISPLAY DEFAULT=${REMOTEHOST}:0.0 OVERRIDE=${DISPLAY}
Now some simple variables
-
PAGER DEFAULT=less MANPAGER DEFAULT=less LESS DEFAULT="M q e h15 z23 b80" NNTPSERVER DEFAULT=localhost PATH DEFAULT=${HOME}/bin:/usr/local/bin:/bin\ :/usr/bin:/usr/local/bin/X11:/usr/bin/X11
Silly examples of escaped variables, just to show how they work.
-
DOLLAR DEFAULT=\$ DOLLARDOLLAR DEFAULT= OVERRIDE=\$${DOLLAR} DOLLARPLUS DEFAULT=\${REMOTEHOST}${REMOTEHOST} ATSIGN DEFAULT="" OVERRIDE=\@
SEE ALSO
AUTHOR
pam_env was written by Dave Kinchlea<EMAIL_ADDRESS>Index
This document was created by man2html, using the manual pages.
Time: 05:34:00 GMT, December 24, 2015


astro.js
J2000
XXX:XX:XX
Reset
—————————————
Current Time
Paused
—————————————
J2000 (0)
—————————————
2016-03-09 Total Solar Eclipse
2017-08-21 Total Solar Eclipse
2019-07-02 Total Solar Eclipse
2020-12-14 Total Solar Eclipse
2024-04-08 Total Solar Eclipse
—————————————
2005-10-03 Annular Solar Eclipse
2016-09-01 Annular Solar Eclipse
2021-06-10 Annular Solar Eclipse
—————————————
2011-12-10 Total Lunar Eclipse
2015-09-28 Total Lunar Eclipse
2016-03-23 Penumbral Lunar Eclipse
2016-09-16 Penumbral Lunar Eclipse
2017-02-11 Penumbral Lunar Eclipse
2018-01-31 Total Lunar Eclipse
2018-07-27 Total Lunar Eclipse
—————————————
1969-07-24 Apollo 11 Landing
DSCOVR Moon Transit 2015
2016111-1200
DSCOVR Moon Occultation, Oct. 2020
DSCOVR Moon Transit Feb. 2021
September 2005
—————————————
Custom
Bright Stars
Dim Stars
Constellations
Clouds
Atmosphere
Close Moon
Zoom
Field of View
Camera
Orbit Earth
Orbit Moon
—————————————
Moon at Earth
Moon at Sun
Apollo 11 at Earth
—————————————
DSCOVR (L1) at Earth
MSG3 at Earth
MET7 at Earth
GOES13 at Earth
GOES15 at Earth
MTSAT3 at Earth
—————————————
DSCOVR (L1) at Moon
Earth at Moon
Baltimore at Moon
—————————————
Earth at Sun
Baltimore at Sun
—————————————
Santa Monica at Sun
Santa Monica Geo
—————————————
Baltimore at GOES13
—————————————
Baltimore Eastern Sky
—————————————
Earth and Moon
Western Sats
—————————————
OTS Moon at Earth
OTS Moon at Sun
OTS Earth at Moon
OTS Earth at Sun
OTS GOES13 at Earth
OTS GOES15 at Earth
Validation:
EPIC/DSCOVR
What the Earth looks like right now
What the Moon looks like right now
Lunar Librationin September, 2005
Online Planetarium
March 2016 Solar Eclipse from DSCOVR
August 2017 Solar Eclipse from DSCOVR
2016111-1200/GOES13
Reference:
Eclipse Dates and Descriptions
Credits:
star and constellations maps
: NASA/Goddard Space Flight Center Scientific Visualization Studio. Constellation figures based on those developed for the IAU by Alan MacRobert of Sky and Telescope magazine (Roger Sinnott and Rick Fienberg).
moon map
: By Jens Meyer
earth daytime map
: Blue Marble


Data collection and processing
Location:
Where Note collects location data from sources such as GPS, Wi-Fi and cell towers once you install the App and consent to the App’s tracking your location. We also collect Accelerometer samples, Wi-Fi network IDs, activity data, and places you identify with the Services. You may choose to stop our collection of location data through the Settings, or by removing the App from your phone.
Do we collect your information?
NO!
All the gps location data is only stored on your device memory and we niether have means nor the intention to collect that data.


{% extends "layout.html" %} {% block page_title %} Question page {% endblock %} {% block content %} When are you travelling? Your exact journey will be printed in your emergency travel document Departure date Date of departure For example, 7 3 2016 Day Month Year Arrival date if different from above (optional) Date of arrival For example, 7 3 2016 Day Month Year Which mode(s) of transport will you use when crossing borders? What is your nationality? Plane Train Boat Car Coach Other Why do you need to travel? Why do you need to travel? To return home For business purposes Going on holiday To visit friends or family To apply for a new passport Compassionate reasons Other If other, tell us the reason next {% endblock %}
Your exact journey will be printed in your emergency travel document
For example, 7 3 2016
next


Title Mr Mrs Miss
First name
Last name
Email
Phone number
Password
Confirm your password
Country Canada France Germany Italy Japan Russia United Kingdom United States
I agree to the terms and conditions
Sign up


Build started {{build.status.started | age}} Build paused {{build.status.started | age}} Idle since {{build.status.started | age}}
Build started {{build.status.started | age}} Build paused {{build.status.started | age}}
Build started {{build.status.started | age}} Build paused {{build.status.started | age}}


Cuba
Havana
Havana's streets are lined with beautiful old, colorful buildings, vintage cars, tiny hooded motocycle cabs and the occasional horse and buggy. There is plenty to do and see so be ready for whatever comes your way! Wander down the street without a plan. Maybe this ends up as a nice walk but more than likely you will stumble upon things to do you didn't know you wanted to do.
Take a walk down El Malecon
El Malecon is a paved road that takes you along the coast where you can enjoy the ocean waves crashing against the shore. It is similar to Chicago's Lake Shore drive. Stop in a gas station and grab an ice cream for the walk or sit outside at Hotel Nacional and drink a fresh mojito and watch the sun set over the ocean.
Find a street party
Talk to some locals and follow them to a party in the street. These are not advertised but are known by word of mouth. You will hear the music and the crowd getting louder as you walk down the small cobblestne streets until you round the corner and find the street packed with people dancing and singing along with the band. Duck into one of the doors and you may find a small bar, grab a drink and head outside to watch the band.
Go salsa dancing
Take a class or just go to the bars and watch others. There are plenty of spots for a great night out. Havana stays open all night! A couple of the popular places are Casa de la Musica and Cafe Cantante but the best way to enjoy the city is to just wander down the street until a place pops up in front of you, you hear the music inside and you take that opportunity and go inside. Keep an open mind and stumble upon something great!
Check out some history
Old Havana is the core of the original city and an UNESCO World Heritage site. It was founded in 1519 and has 5 large plazas each with their own style. Old havana is defined by the old city walls. Morro Castle is the old fortress guarding the entrance to Havana Bay. It was built in 1589 in response to raids. NOw you can go inside and check out the exhibiions. Museum of the Revolution became a museum after the Cuban Revoluion and is located in the old Presidential Palace. These are just a few places amongst many more!


fetch-json v
A wrapper around Fetch just for JSON
Why would you fetch anything but json? ;)
fetch-json makes REST easy — it automatically:
- Converts the HTTP response to JSON if it's not already JSON
- Serializes the body payload with
JSON.stringify()
- Adds the
'application/json'
HTTP header to set the data type - Appends the GET
params
object items to the URL - Runs
.json()
on the response - Sets
credentials
to'same-origin'


IDelegation is an interface for contracts that implement a governance system in which a group of elected accounts is allowed to rule one or more controled registers contract. It allows to implement a repesentativ democracy system in which representatives (delegation members) mandate and decisions can be canceled via direct democracy. Delegation.sol contract is an implementation of this interface. By implementing this interface you can develop your own custom Delegations and plug them into a DAO project via the Constitution contract.
Functions
When the voting period is over, any citizen can call this function to end the voting stage. If the winning proposition is the default proposition is the default one (Proposition 0) the law proejct is aborted. Otherwise, the Law Censoring stage is started.
| Name | Type | Description |
|---|---|---|
| law_project | bytes32 | Id of the law project the caller wants to add a proposition to. The Id is obtained by hashing the Title with the Description of the law project. |
Returns:
No parameters
Function used to add a register contract under the control of current delegation.
| Name | Type | Description |
|---|---|---|
| register_address | address | Address of the register contract that can now be ruled by current delegation |
Returns:
No parameters
Function can be called by a delegation member to modify a proposition that he has already created (He have to be the author of the proposition). Caller must approve {FunctionCall_Price} (see {Law_Project_Parameters} struct of {Delegation_Uils library}) multiplied by the number of function call he wants to add to the proposition, token for Delegation contract.
| Name | Type | Description |
|---|---|---|
| law_project | bytes32 | Id of the law project the caller wants to add a proposition to. The Id is obtained by hashing the Title with the Description of the law project. |
| Proposal | uint256 | Proposition Id to modify. |
| New_Items | bytes[] | Array of new function calls to add to the Proposition. |
| Indexs | uint256[] | array of Proposition's function call list indexs to inser new function call (contained in {New_Items}) to. {New_Items} and {Indexs} have the same length. |
Returns:
No parameters
Function can be called by a delegation member to submit a new law project. This function put {Law_Initialisation_Price} (see {Law_Project_Parameters} struct of {Delegation_Uils library}) DemoCoin token of Delegation contract in Escrow.
| Name | Type | Description |
|---|---|---|
| register_address | address | Address of the register contract the law project is about. Must be contained in Controled_Registers mapping. |
| Title | bytes | Title of the law project. Can be an hash. |
| Description | bytes | Text explaining the spirit and generals goals of the law project. Can be an hash. |
Returns:
No parameters
Function can be called by a delegation member to submit a corpus of function calls propositions to an existing pending law project. This function put in Escrow {FunctionCall_Price} (see {Law_Project_Parameters} struct of {Delegation_Uils library}) DemoCoin token multiplied by the number of function call contained in the proposition.
| Name | Type | Description |
|---|---|---|
| law_project | bytes32 | Id of the law project hte caller wants to add a proposition to. The Id is obtained by hashing the Title with the Description of the law project. |
| Parent | uint256 | Proposition Id the caller wants to attach his proposition to. It's the parent proposition in the proposal tree. If there isn't any proposition in the tree we want to attach the new proposition to, we set Parent to 0 |
| Parent_Proposals_Reuse | uint256[] | List of Parent's function calls index we want to reuse in the new proposition. Function calls are ordered in the order we want them to be executed. 0 elements correspond to new function calls that have to be added by the caller in {New_Function_Call} argument. |
| New_Function_Call | bytes[] | List of new function calls added by the caller. For each element of the New_Function_Call array, caller must set a 0 element in {Parent_Proposals_Reuse} array at the index he want the custom function call to be positioned |
| Description | bytes | Text to justify the new proposal. Can be an hash. |
Returns:
No parameters
If the Law censor period is over and the law project hasn't been rejected by citizens, then any delegation member can call this function to set the law project as ADOPTED (see {Status} enumeration).
| Name | Type | Description |
|---|---|---|
| law_project | bytes32 | Id of the law project the caller wants to add a proposition to. The Id is obtained by hashing the Title with the Description of the law project. |
Returns:
No parameters
Function called by a citizen who wish to candidate to next mandate's elections.
No parameters
Returns:
No parameters
If we are at the Law censor stage, any citizen can call this function to sign the petition for canceling the law project. If the {Censor_Proposition_Petition_Rate} (see {Law_Project_Parameters} structure) is reached, the law project is aborted.
| Name | Type | Description |
|---|---|---|
| law_project | bytes32 | Id of the law project the caller wants to add a proposition to. The Id is obtained by hashing the Title with the Description of the law project. |
Returns:
No parameters
Allows to check if an account belong to current delegation
| Name | Type | Description |
|---|---|---|
| member_address | address | address of the account we want to check whether it belongs to current delegation or not. |
Returns:
| Name | Type | Description |
|---|---|---|
| contain | bool |
When voting stage is over, any citizen can call this function to end the election and start a new mandate.
No parameters
Returns:
No parameters
Once the law project has been adopted (ADOPTED value of {Status} enum) then any delegation member can call this function to execute all or some of the remaining function call of the winning proposition. For the law project to be fully executed all function call have to be executed.
| Name | Type | Description |
|---|---|---|
| law_project | bytes32 | Id of the law project the caller wants to add a proposition to. The Id is obtained by hashing the Title with the Description of the law project. |
| num_function_call_ToExecute | uint256 | Number of function calls to execute. |
Returns:
No parameters
When the current mandate duration is over or if the {New_Election_Petition_Rate} (see {Mandate} struct of {Delegation_Uils} library) is reached, any citizen can call this function to start a new election
No parameters
Returns:
No parameters
Function called by a citizen who wish to remove his candidature from next mandate's elections.
No parameters
Returns:
No parameters
Function used to remove the control of a register contract from current delegation.
| Name | Type | Description |
|---|---|---|
| register_address | address | Address of the register contract that isn't rulable anymore by current delegation |
Returns:
No parameters
Function can be called by a citizen to sign petition for a new election
No parameters
Returns:
No parameters
When the period of proposition submiting is over, any citizen can call this function to start the voting stage. The Id of the ballot corresponding to current law project the IVote contract is computed by hashing {law_project} Id with current block timestamps.
| Name | Type | Description |
|---|---|---|
| law_project | bytes32 | Id of the law project the caller wants to add a proposition to. The Id is obtained by hashing the Title with the Description of the law project. |
Returns:
No parameters
Change parameters related to the democratic process of Delegation's members election.
| Name | Type | Description |
|---|---|---|
| Election_Duration | uint256 | Duration of the stage in which citizens are allowed to vote for Candidats they prefer |
| Validation_Duration | uint256 | Duration of the stage in which citizens can validate their hased vote by revealing their choice and the salt that has been used for hasing |
| Mandate_Duration | uint256 | Duration of a delegation mandate |
| Immunity_Duration | uint256 | Amount of time after the beginning of a new mandate during which delegation's members can't be revoked |
| Num_Max_Members | uint16 | Maximum number of members in the delegation. |
| New_Election_Petition_Rate | uint16 | The minimum ratio of citizens required to revoke the current delegation's members and start a new election |
| Ivote_address | address | Address of the IVote contract that will be used during election stage |
Returns:
No parameters
Change parameters related to the democratic process of registers governance.
| Name | Type | Description |
|---|---|---|
| Uint256_Legislatifs_Arg | uint256[6] | It's an array (We use an array to prevent the "stack to deep error") of uint256 arguments representing respectively: - Member_Max_Token_Usage: The maximum amount of token a member is allowed to use for a law project elaboration - Law_Initialisation_Price: The price in token for creating a law project - FunctionCall_Price: The price in token for one FunctionCall. - Proposition_Duration: The duration of the stage in which members are allowed to submit propositions - Vote_Duration: The duration of the stage in which members are allowed to vote for the proposition they want - Law_Censor_Period_Duration: The duration of the stage in which all citizens are allowed to sign a etition against the law project proposed by the Delegation |
| Censor_Proposition_Petition_Rate | uint16 | The minimum ratio of citizens required to cancel a law project |
| Censor_Penalty_Rate | uint16 | Ratio of total amount of token belonged by the delegation that will be lost if a law project is rejected by citizens |
| Ivote_address | address | Address of the IVote contract that will be used during voting stage |
Returns:
No parameters


ROSSANA GODFREY
Sociologist, English-Spanish Interpreter
and aspiring web developer.
Sometimes photographer and pet sitter
Marketing professional with more than eight years
of experience in the television industry,
data audience analysis and market research.
Goal-oriented, high-achiever with extensive
and wide-ranging experience in providing advanced
customer service as well as communication and
organizational expertise.
Innovative entrepreneurial business leader with the
proven ability to maximize and streamline business plans.
Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor
incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud
exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat.
Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore
eu fugiat nulla pariatur.Excepteur sint occaecat cupidatat non proident,
sunt in culpa qui officia deserunt mollit anim id est laborum."


Sign Up
Already havean account?
Sign In
Email Address
Password
Forgot Password
Or
Sign in with Google
Sign in with Facebook
Sign in with Apple


library(dplyr)
##
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
##
## filter, lag
## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union
library(Hurricanes)
Hurricanes
is intended to give easy access to hurricane archives. In short, it is a web-scraping tool that parses the National Hurricane Center’s (NHC) archives to get storm data.
At this point, data is only available back to 1998.
There are two basins which data is available: north Atlantic (“AL”) and northeastern Pacific (“EP”). The northeastern Pacific basin typically covers from the west coast of North America to -140° longitude (140°W). The Central Pacific Hurricane Center (CPHC) covers the north Pacific from -140° to -180°.
The NHC will stop issuing advisories once a storm crosses -140° where the CPHC takes over. However, I cannot rule out that some storms that have crossed this “boundary” or even developed in CPHC waters will not exist in records retrieved.
On a semi-related note. In some instances (such as Hurricane Otto, 2016) a storm may cross from the Atlantic to Pacific ocean (and even vice versa, though rare). When this happens the storm is given a new name once it emerges into the Pacific ocean. However, if a storm crosses -140° longitude it retains it’s name.
Lastly, it is possible a storm will develop at the end of the year and continue to exist into the next year. I am not aware if those storms will exist in this package as of this time. However, generally the storm should be listed in the archives of the year it developed.
By default, get_storms
will return all storms that have developed for the current year in both basins. If no storms have developed, an error will be generated. For this example, we’ll use 2016.
al.2016 <- get_storms(year = 2016, basin = "AL") %>% tbl_df %>% print(n = nrow(.))
## # A tibble: 16 x 4
## Year Name Basin
## <dbl> <chr> <chr>
## 1 2016 Hurricane Alex AL
## 2 2016 Tropical Storm Bonnie AL
## 3 2016 Tropical Storm Colin AL
## 4 2016 Tropical Storm Danielle AL
## 5 2016 Hurricane Earl AL
## 6 2016 Tropical Storm Fiona AL
## 7 2016 Hurricane Gaston AL
## 8 2016 Tropical Depression Eight AL
## 9 2016 Hurricane Hermine AL
## 10 2016 Tropical Storm Ian AL
## 11 2016 Tropical Storm Julia AL
## 12 2016 Tropical Storm Karl AL
## 13 2016 Tropical Storm Lisa AL
## 14 2016 Hurricane Matthew AL
## 15 2016 Hurricane Nicole AL
## 16 2016 Hurricane Otto AL
## # ... with 1 more variables: Link <chr>
You can also gather multiple years.
get_storms(year = 2014:2015, basin = "EP")
get_storm_data
can be used to retrieve one or multiple products for a specific cyclone.
Load forecast/advisory data for Hurricane Hermine:
url <- al.2016 %>% filter(Name == "Hurricane Hermine") %>% .$Link
get_storm_data("fstadv", link = url)
## [1] TRUE
This call brings a dataframe to the global environment: fstadv
:
head(fstadv)
## # A tibble: 6 x 125
## Key Adv Date Name Status Lat
## <chr> <chr> <dttm> <chr> <chr> <dbl>
## 1 AL092016 1 2016-08-28 21:00:00 Nine Tropical Depression 23.7
## 2 AL092016 2 2016-08-29 03:00:00 Nine Tropical Depression 23.4
## 3 AL092016 3 2016-08-29 09:00:00 Nine Tropical Depression 23.5
## 4 AL092016 4 2016-08-29 15:00:00 Nine Tropical Depression 23.6
## 5 AL092016 5 2016-08-29 21:00:00 Nine Tropical Depression 24.0
## 6 AL092016 6 2016-08-30 03:00:00 Nine Tropical Depression 23.9
## # ... with 119 more variables: Lon <dbl>, Wind <dbl>, Gust <dbl>,
## # Pressure <dbl>, PosAcc <dbl>, FwdDir <dbl>, FwdSpeed <dbl>, Eye <dbl>,
## # NE34 <dbl>, SE34 <dbl>, SW34 <dbl>, NW34 <dbl>, NE50 <dbl>,
## # SE50 <dbl>, SW50 <dbl>, NW50 <dbl>, NE64 <dbl>, SE64 <dbl>,
## # SW64 <dbl>, NW64 <dbl>, SeasNE <dbl>, SeasSE <dbl>, SeasSW <dbl>,
## # SeasNW <dbl>, Hr12FcstDate <dttm>, Hr12Lat <dbl>, Hr12Lon <dbl>,
## # Hr12Wind <dbl>, Hr12Gust <dbl>, Hr12NE34 <dbl>, Hr12SE34 <dbl>,
## # Hr12SW34 <dbl>, Hr12NW34 <dbl>, Hr12NE50 <dbl>, Hr12SE50 <dbl>,
## # Hr12SW50 <dbl>, Hr12NW50 <dbl>, Hr12NE64 <dbl>, Hr12SE64 <dbl>,
## # Hr12SW64 <dbl>, Hr12NW64 <dbl>, Hr24FcstDate <dttm>, Hr24Lat <dbl>,
## # Hr24Lon <dbl>, Hr24Wind <dbl>, Hr24Gust <dbl>, Hr24NE34 <dbl>,
## # Hr24SE34 <dbl>, Hr24SW34 <dbl>, Hr24NW34 <dbl>, Hr24NE50 <dbl>,
## # Hr24SE50 <dbl>, Hr24SW50 <dbl>, Hr24NW50 <dbl>, Hr24NE64 <dbl>,
## # Hr24SE64 <dbl>, Hr24SW64 <dbl>, Hr24NW64 <dbl>, Hr36FcstDate <dttm>,
## # Hr36Lat <dbl>, Hr36Lon <dbl>, Hr36Wind <dbl>, Hr36Gust <dbl>,
## # Hr36NE34 <dbl>, Hr36SE34 <dbl>, Hr36SW34 <dbl>, Hr36NW34 <dbl>,
## # Hr36NE50 <dbl>, Hr36SE50 <dbl>, Hr36SW50 <dbl>, Hr36NW50 <dbl>,
## # Hr36NE64 <dbl>, Hr36SE64 <dbl>, Hr36SW64 <dbl>, Hr36NW64 <dbl>,
## # Hr48FcstDate <dttm>, Hr48Lat <dbl>, Hr48Lon <dbl>, Hr48Wind <dbl>,
## # Hr48Gust <dbl>, Hr48NE34 <dbl>, Hr48SE34 <dbl>, Hr48SW34 <dbl>,
## # Hr48NW34 <dbl>, Hr48NE50 <dbl>, Hr48SE50 <dbl>, Hr48SW50 <dbl>,
## # Hr48NW50 <dbl>, Hr48NE64 <dbl>, Hr48SE64 <dbl>, Hr48SW64 <dbl>,
## # Hr48NW64 <dbl>, Hr72FcstDate <dttm>, Hr72Lat <dbl>, Hr72Lon <dbl>,
## # Hr72Wind <dbl>, Hr72Gust <dbl>, Hr72NE34 <dbl>, Hr72SE34 <dbl>,
## # Hr72SW34 <dbl>, ...
We can get the forecast/advisory data and wind speed probabilities at once:
get_storm_data("fstadv", "wndprb", link = url)
## [1] TRUE
We now have two dataframes in our global environment: fstadv
and wndprb
.
dim(fstadv)
## [1] 38 125
dim(wndprb)
## [1] 2251 18
You can pass preferred values for names of each dataframe returned.
get_storm_data("fstadv", "wndprb",
names = list("fstadv" = "al.09.2016.fstadv",
"wndprb" = "al.09.2016.wndprb"),
link = url)
## [1] TRUE
dim(al.09.2016.fstadv)
## [1] 38 125
dim(al.09.2016.wndprb)
## [1] 2251 18
fstadv
)The core of a storm’s dataset is located in the Forecast/Advisory product. This product contains current location, forecast position, movement and structural detail of the cyclone.
al.09.2016 <- get_fstadv(link = url)
The dataframe returned is rather wide:
dim(al.09.2016)
## [1] 38 125
There is a function that will break the dataframe down into four narrow frames; each with it’s own purpose. Let’s look at that and then I’ll go over the variables returned.
fstadv_split("al.09.2016")
## [1] TRUE
The fstadv_split
function takes the name of the dataframe in character format. The original dataframe is then split up and each “child” dataframe receives the same name with it’s purpose appended to the name. In this instance, al.09.2016
remains the parent dataframe but it is much more narrow:
dim(al.09.2016)
## [1] 38 18
And our child dataframes:
dim(al.09.2016.wr)
## [1] 49 8
dim(al.09.2016.fst)
## [1] 249 8
dim(al.09.2016.fst.wr)
## [1] 287 9
In this example, al.09.2016
is our parent dataframe. It contains the core data for each advisory listed for this particular cyclone.
str(al.09.2016)
## Classes 'tbl_df', 'tbl' and 'data.frame': 38 obs. of 18 variables:
## $ Key : chr "AL092016" "AL092016" "AL092016" "AL092016" ...
## $ Adv : chr "1" "2" "3" "4" ...
## $ Date : POSIXct, format: "2016-08-28 21:00:00" "2016-08-29 03:00:00" ...
## $ Name : chr "Nine" "Nine" "Nine" "Nine" ...
## $ Status : chr "Tropical Depression" "Tropical Depression" "Tropical Depression" "Tropical Depression" ...
## $ Lat : num 23.7 23.4 23.5 23.6 24 23.9 23.8 24 24.4 24.3 ...
## $ Lon : num -81.7 -82.7 -83.9 -84.3 -84.8 -85.5 -86.6 -87.2 -87.3 -87.8 ...
## $ Wind : num 30 30 30 30 30 30 30 30 30 30 ...
## $ Gust : num 40 40 40 40 40 40 40 40 40 40 ...
## $ Pressure: num 1009 1007 1007 1007 1007 ...
## $ PosAcc : num 25 25 20 25 25 20 20 25 20 20 ...
## $ FwdDir : num 270 270 275 280 290 280 275 290 320 345 ...
## $ FwdSpeed: num 8 8 8 6 4 6 6 6 4 2 ...
## $ Eye : num NA NA NA NA NA NA NA NA NA NA ...
## $ SeasNE : num NA NA NA NA NA NA NA NA NA NA ...
## $ SeasSE : num NA NA NA NA NA NA NA NA NA NA ...
## $ SeasSW : num NA NA NA NA NA NA NA NA NA NA ...
## $ SeasNW : num NA NA NA NA NA NA NA NA NA NA ...
The variables Key
, Adv
and Date
should be used if you wish to join this parent data frame with any of the child dataframes.
Any cyclone of at least tropical storm-strength will have associated wind field values.
str(al.09.2016.wr)
## Classes 'tbl_df', 'tbl' and 'data.frame': 49 obs. of 8 variables:
## $ Key : chr "AL092016" "AL092016" "AL092016" "AL092016" ...
## $ Adv : chr "13" "14" "14" "15" ...
## $ Date : POSIXct, format: "2016-08-31 21:00:00" "2016-09-01 03:00:00" ...
## $ WindField: num 34 34 50 34 50 34 50 34 50 34 ...
## $ NE : num 110 110 20 120 20 120 60 150 100 150 ...
## $ SE : num 110 110 20 120 20 120 60 160 120 160 ...
## $ SW : num 0 90 0 60 0 60 0 60 30 60 ...
## $ NW : num 0 0 0 0 0 40 0 60 30 60 ...
head(al.09.2016.wr)
## # A tibble: 6 x 8
## Key Adv Date WindField NE SE SW NW
## <chr> <chr> <dttm> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 AL092016 13 2016-08-31 21:00:00 34 110 110 0 0
## 2 AL092016 14 2016-09-01 03:00:00 34 110 110 90 0
## 3 AL092016 14 2016-09-01 03:00:00 50 20 20 0 0
## 4 AL092016 15 2016-09-01 09:00:00 34 120 120 60 0
## 5 AL092016 15 2016-09-01 09:00:00 50 20 20 0 0
## 6 AL092016 16 2016-09-01 15:00:00 34 120 120 60 40
In the example above you can see that for advisory #13, this cyclone had one-minute sustained wind speeds of at least 34 kts spread out 110 nautical miles to the northeast of the center of circulation, 110 nautical miles to the southeast, but 0 miles in both the southwest and northwest quadrant. (This is not unusual as many weak cyclones are assymetric in some fashion.)
On advisory #14 there are two rows of data: one for the 34kt wind field and another for the 50kt wind field (a third, 64kt, will be present for hurricanes).
You can identify that on this advisory the storm system has expanded it’s circulation into the southwestern quadrant but still hasn’t wrapped around to encompass the northwestern quadrant. The radius of 50kt winds remains tightly around the center in the eastern quadrant.
Note that if a storm is not of tropical storm-strength, this data will not exist.
Most Forecast/Advisory products will have forecast data associated with it unless the storm is expected to dissipate very soon or already has. This data can be found in al.09.2016.fst
.
Each forecast/advisory product can have many (or none) forecast positions. And this number has changed over the years. Originally forecasts were only issued for 72 hours but this has expanded now to 120 hours.
Forecasts exist for every 12-hour period up to 48 hours. After that time, a forecast will be available for sequential 24-hour periods; i.e., 12, 24, 36, 48, 72, 96 and 120.
str(al.09.2016.fst)
## Classes 'tbl_df', 'tbl' and 'data.frame': 249 obs. of 8 variables:
## $ Key : chr "AL092016" "AL092016" "AL092016" "AL092016" ...
## $ Adv : chr "1" "1" "1" "1" ...
## $ Date : POSIXct, format: "2016-08-28 21:00:00" "2016-08-28 21:00:00" ...
## $ FcstDate: POSIXct, format: "2016-08-29 06:00:00" "2016-08-29 18:00:00" ...
## $ Lat : num 23.9 24.3 24.6 25.1 26.8 29 31 23.5 23.8 24.4 ...
## $ Lon : num -83.6 -85.4 -86.8 -87.6 -87.4 -84.5 -80 -84 -85.4 -86.8 ...
## $ Wind : num 30 35 35 40 45 45 45 30 35 35 ...
## $ Gust : num 40 45 45 50 55 55 55 40 45 45 ...
Some forecast positions may also contain wind radius information (only up to 72 hours). This data can be found in al.09.2016.fst.wr
. It’s structure is very similar to al.2019.2016.wr
.
str(al.09.2016.fst.wr)
## Classes 'tbl_df', 'tbl' and 'data.frame': 287 obs. of 9 variables:
## $ Key : chr "AL092016" "AL092016" "AL092016" "AL092016" ...
## $ Adv : chr "1" "1" "1" "1" ...
## $ Date : POSIXct, format: "2016-08-28 21:00:00" "2016-08-28 21:00:00" ...
## $ FcstDate : POSIXct, format: "2016-08-29 18:00:00" "2016-08-30 06:00:00" ...
## $ WindField: num 34 34 34 34 34 34 34 34 34 34 ...
## $ NE : num 30 30 50 60 30 40 50 60 40 40 ...
## $ SE : num 0 0 30 60 0 20 30 50 0 20 ...
## $ SW : num 0 0 0 40 0 0 20 30 0 0 ...
## $ NW : num 30 30 40 50 30 30 40 50 40 30 ...
You can join this dataframe to al.09.2016.fst
by the Key
, Adv
, Date
and FcstDate
variables.
Please see the National Hurricane Center’s website for more information on understanding the Forecast/Advisory product.
prblty
)Strike probabilities were discontinued after the 2005 hurricane season. For this example, we’ll look at Hurricane Katrina. For this we use the function get_prblty
.
al.2005 <- get_storms(year = 2005, basin = "AL")
url <- al.2005 %>% filter(Name == "Hurricane Katrina") %>% .$Link
al.12.2016.prblty <- get_prblty(link = url)
str(al.12.2016.prblty)
## Classes 'tbl_df', 'tbl' and 'data.frame': 937 obs. of 10 variables:
## $ Status : chr "Tropical Depression" "Tropical Depression" "Tropical Depression" "Tropical Depression" ...
## $ Name : chr "Twelve" "Twelve" "Twelve" "Twelve" ...
## $ Adv : chr "1" "1" "1" "1" ...
## $ Date : POSIXct, format: "2005-08-23 21:00:00" "2005-08-23 21:00:00" ...
## $ Location: chr "25.0N 77.7W" "JACKSONVILLE FL" "25.7N 78.5W" "SAVANNAH GA" ...
## $ A : num 50 0 36 0 19 0 0 0 0 0 ...
## $ B : num 0 0 0 0 6 0 1 0 0 5 ...
## $ C : num 0 2 0 0 1 0 0 0 0 3 ...
## $ D : num 0 9 1 6 1 3 3 2 2 5 ...
## $ E : num 50 11 37 6 27 3 4 2 2 13 ...
This dataframe contains the possibility of a cyclone passing within 65 nautical miles of Location
. The variables A
, B
, C
, D
, and E
are as they appear in the products and were left as-is to avoid confusion. They’re definition is as follows:
A
- current through 12 hours.B
- within the next 12-24 hoursC
- within the next 24-36 hoursD
- within the next 36-48 hoursE
- Total probability from current through 48 hours.Many values in the text product may be “X” for less than 1% chance of a strike. These values are converted to 0 as the fields are numeric.
The strike probability products did not contain Key
which is the unique identifier for every cyclone. So the best way to do any joins will be by Name
, Adv
and Date
.
Strike Probabilities may not exist for most Pacific cyclones.
wndprb
)url <- al.2016 %>% filter(Name == "Hurricane Hermine") %>% .$Link
al.09.2016.wndprb <- get_wndprb(link = url)
str(al.09.2016.wndprb)
## Classes 'tbl_df', 'tbl' and 'data.frame': 2251 obs. of 18 variables:
## $ Key : chr "AL092016" "AL092016" "AL092016" "AL092016" ...
## $ Adv : chr "1" "1" "1" "1" ...
## $ Date : POSIXct, format: "2016-08-28 21:00:00" "2016-08-28 21:00:00" ...
## $ Location : chr "ELIZABETH CTY" "RALEIGH NC" "ROCKY MT NC" "CAPE HATTERAS" ...
## $ Wind : num 34 34 34 34 34 34 34 34 34 34 ...
## $ Wind12 : num 0 0 0 0 0 0 0 0 0 0 ...
## $ Wind24 : num 0 0 0 0 0 0 0 0 0 0 ...
## $ Wind24Cum : num 0 0 0 0 0 0 0 0 0 0 ...
## $ Wind36 : num 0 0 0 0 0 0 0 0 0 0 ...
## $ Wind36Cum : num 0 0 0 0 0 0 0 0 0 0 ...
## $ Wind48 : num 0 0 0 0 0 0 0 0 0 0 ...
## $ Wind48Cum : num 0 0 0 0 0 0 0 0 0 0 ...
## $ Wind72 : num 0 0 0 0 0 0 0 0 0 0 ...
## $ Wind72Cum : num 0 0 0 0 0 0 0 0 0 0 ...
## $ Wind96 : num 0 0 0 0 0 0 0 0 0 0 ...
## $ Wind96Cum : num 0 0 0 0 0 0 0 0 0 0 ...
## $ Wind120 : num 3 3 3 5 5 3 5 6 6 7 ...
## $ Wind120Cum: num 3 3 3 5 5 3 5 6 6 7 ...
Wind Speed Probabilities are a bit more advanced than their predecessor. The Wind
variable is for 34kt, 50kt and 64kt winds expected within a specific time period.
Each consecutive variable is within a specific time-frame (12, 24, 36, 48, 72, 96 and 120 hours) for both that time frame and cumulative.
For example, Wind24
is the chance of Wind
between 12-24 hours. Wind24Cum
is the cumulative probability from Date
through 24 hours.
As with strike probabilities, an “X” in the original text product meant less than 0.5% chance for the specified wind in the specified time period. “X” has been replaced by 0 in this package.
Strike Probabilities may not exist for most Pacific cyclones.
See Tropical Cyclone Wind Speed Probabilities Products for more information.
Other products are available:
get_public
for Public Advisory statements. Think general information for the public audience. May not exist for some Pacific cyclones. Additionally, when watches and warnings are issued, these are issued every 3 hours (and, in some cases, every two).
get_discus
for Storm Discussions. These are more technical statements on the structure of a storm, forecast model tendencies and satellite presentation.
get_update
These are brief update statements when something considerable has changed in the cyclone or if the cyclone is making landfall.
get_posest
. Position estimates are generally issued when a storm is making landfall and may be issued hourly.
Hurricane Ike, 2008, has both updates and position estimates.
At this time none of these products are parsed. Only the content of the product is returned.


1. Paste web or spreadsheet table below
2. Select desired section above
3. Edit and copy from here:
Tablas simples allows you to easily produce tables in plain text (Markdown or otherwise) for your emails or documents by copying and pasting a table or spreadsheet from the web or from LibreOffice Calc or Excel. After pasting, select the columns you need and ASCII or Markdown comes out. Good for taming unwieldy and complex tables you need to forward on emails or to copy just a section of it.
Copy and paste the table in the first space, then select just the columns you need and a simple table appears in the second space ready for you to copy and paste into your text editor, Markdown document or email. Header borders are automatically added to the top row.
I like plain text. Sometimes I want to easily copy and paste tables and spreadsheets into emails or text documents. Specifically, I needed to forward flight itineraries on email which I was getting on ugly HTML tables. There are similar tools, such as ASCII table generator, markdownTables, Markdown tables generator, Markdown-table and the closed source Table to markdown, but I needed something that could handle colspans and multi-line cells as well as balancing column widths. This is still missing automatic line wraps (for example, to make the table fit in 80 columns of plain text) and rowspans.
Tablas simples is all Javascript with jquery running in the client. It uses the Turndown HTML to Markdown converter and Selection.js for x/y selection to pick just the section of the table tou nees. I also use RequireJS to make it easier for me, but it could probably be done without it, a modified version of the Joplin Turndown plugin, itself a fork of the turndown-plugin-gfm for Github-flavored Markdown, and DOMPurify to sanitize the input.
Get the source code here. Get in touch here or check my Twitter at @mir_lentejas.