weather_data | downloading weather data : satellite
kandi X-RAY | weather_data Summary
kandi X-RAY | weather_data Summary
Scripts of downloading weather data (satellite and reanalysis data). Please check README.md files under each directory for detailed usage.
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weather_data Key Features
weather_data Examples and Code Snippets
Lines of Code : 29License : Permissive (MIT License)
Copydef display_weather_info(weather_data, imperial=False):
"""Prints formatted weather information about a city.
Args:
weather_data (dict): API response from OpenWeather by city name
imperial (bool): Whether or not to use imperi def display_weather_info(weather_data, imperial=False):
"""Prints formatted weather information about a city.
Args:
weather_data (dict): API response from OpenWeather by city name
imperial (bool): Whether or not to use imperi Community Discussions
Trending Discussions on weather_data
QUESTION
data = pandas.read_csv("weather_data.csv")
print(data)
print(data[data['day'] == 'Monday'])
print(type(data['day']))
print(type(data['day'] == 'Monday'))
ANSWER
Answered 2021-Jun-07 at 07:38A DataFrame is a collection of aligned Series, aligned means that all Series are labeled in the same manner. The common part or labels is called Index and it is nothing more than a pimped Serie.
Operations with Series tend to return a Serie itself, easily it is an element-wise comparison, the result is an array of boolean of the same size and with the same labels a boolean array, called mask.
some example:QUESTION
data = pandas.read_csv("weather_data.csv")
print(type(data['temp'][1]))
ANSWER
Answered 2021-Jun-07 at 04:11From the dependency, it says
NumPy - Adds support for large, multi-dimensional arrays, matrices and high-level mathematical functions to operate on these arrays
So yes, numpy is internally imported in pandas (so the to_numpy function works).
However, you should still import numpy when you want to directly use numpy's functions.
QUESTION
with open("weather_data.csv", 'r') as data_file:
data = csv.reader(data_file)
for x in data:
print(x)
ANSWER
Answered 2021-Jun-07 at 01:57The csv.reader object is its own iterator. This is a common practice for iterables which are single-pass (i.e. can only be run through once). We can confirm this by inspection.
QUESTION
I'm trying to create an R function to impute mean values to specific columns in a data frame.
...ANSWER
Answered 2021-May-16 at 09:47You could try this function?!
QUESTION
I wrote a test to verify the POST was parsed correctly. Here is the endpoint:
...ANSWER
Answered 2021-Apr-01 at 18:40It looks like the error is occurring when trying to unparse the json with serde at let wd: Vec = serde_json::from_str(&*weather_data).unwrap(); and it seems to be related to the timestamps in the json payload. Usually GitHub actions are executed in UTC, which would likely be different from your local computer's clock, which can sometimes cause errors.
It's also possible that the timestamp formats supported on each platform are different, but that depends on the definition of the data structures being deserialized, which isn't shown in the question
QUESTION
I'm trying to predict delays based on weather 2 hours before scheduled travel. I have one dataset of travel data (call df1) and one dataset of weather (call df2). In order to predict the delay, I am trying to join df1 and df2 with an offset of 2 hours. That is, I want to look at the weather data 2 hours before the scheduled travel data. A paired down view of the data would look something like this
example df1 (travel data):
travel_data location departure_time delayed blah KPHX 2015-04-23T15:02:00.000+0000 1 bleh KRDU 2015-04-27T15:19:00.000+0000 0example df2 (weather data):
location report_time weather_data KPHX 2015-01-01 01:53:00 blih KRDU 2015-01-01 09:53:00 blohI would like to join the data first on location and then on the timestamp data with a minimum 2 hour offset. If there are multiple weather reports greater than 2 hours earlier than departure time, I would like to join the travel data with the closest report to a 2 hour offset as possible.
So far I have used
...ANSWER
Answered 2021-Apr-02 at 01:28Change the join condition to be >= and get largest report timestamp after partitioning by location.
QUESTION
I would like to remove files with a certain name from all subdirectories. For example, my working directory is as follows: "main directory/weather_data --> weather data contains the subdirectories D0 and D1. In these subdirectories there are files with the names "rainy weather_D0.txt" and sunny weather_D0.txt". from both subdirectories (D0 and D1) I would like to remove the file with the name "rainy weather.txt"
I have tried to do it like this in R
...ANSWER
Answered 2021-Mar-27 at 12:07Since your text files are in subdirectories of weather_data you need to add the recursive = TRUE argument to list.files() - otherwise it will only find "D0" and "D1". The pattern also will not find the files because $ means end of line, so it will only find files that end with "rainy weather" (and your files begin with it). I suggest changing pattern to just "rainy weather".
QUESTION
i am making an API call to get weather, but i am not able to loop through the results in template also note that i am able to print the result in terminal
Here is my code:
...ANSWER
Answered 2021-Mar-18 at 18:34You're passing the wrong variable into your context here:
QUESTION
When multiplying two columns together in a spark SQL table with random negative values, returns "NaN" for those which have a negative in one of the columns. Any techniques to help get the calculations work?
...ANSWER
Answered 2021-Feb-05 at 19:20QUESTION
I'm trying to make a flask pipeline which receives data from a python file and sends the data to react which display them.
I currently am stuck trying to receive the data in flask after sending them via post to the URL: localhost:5000/weather-data
The data is being posted with this Code:
...ANSWER
Answered 2021-Feb-24 at 21:33Have you tried using json?
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
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Install weather_data
You can use weather_data like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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