Grouper | Python command line tool to manage Azure Network Security | Security library
kandi X-RAY | Grouper Summary
kandi X-RAY | Grouper Summary
A Python 3 command line tool to manage Azure Network Security Group Rules.
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Top functions reviewed by kandi - BETA
- Convert a CSV file to ARM format
- Parse the contents of the CSV file
- Write an ARM template file
- Builds the Nsg_Template from a list of NSG rules
- Import NSG rules from an Azure account
- Returns a dictionary of attribute values
- Reorder a list of preferred order
- Writes the security rules to a csv file
- Create a CLI script from a csv file
- Writes CLI_SCRIPT to file
- Get attribute value by name
- Generates a sample data file
- Load a prefixed preference
- Print a pretty formatted output table
- Create a security rule from a dictionary
Grouper Key Features
Grouper Examples and Code Snippets
Community Discussions
Trending Discussions on Grouper
QUESTION
I grouped a dataframe test_df2
by frequency 'B'
(by business day, so each name of the group is the date of that day at 00:00) and am now looping over the groups to calculate timestamp differences and save them in the dict grouped_bins
. The data in the original dataframe and the groups looks like this:
What I want is to calculate the difference between each row's timestamp
, for example of rows 7
and 0
, since they have the same externalId
.
What I did for that purpose is the following.
...ANSWER
Answered 2021-Jun-14 at 22:22To convert your timestamp strings to a datetime object:
QUESTION
I'm trying to create a multi-page pdf using FacetGrid from this (https://seaborn.pydata.org/examples/many_facets.html). There are 20 grids images and I want to save the first 10 grids in the first page of pdf and the second 10 grids to the second page of pdf file. I got the idea of create mutipage pdf file from this (Export huge seaborn chart into pdf with multiple pages). This example works on sns.catplot() but in my case (sns.FacetGrid) the output pdf file has two pages and each page has all of the 20 grids instead of dividing 10 grids in each page.
...ANSWER
Answered 2021-Jun-14 at 17:16You are missing the col_order=cols
argument to the grid = sns.FacetGrid(...)
call.
QUESTION
I've got a dataframe with power profiles. The dataframe shows start and endtime and consumed power during a transaction. It looks something like this:
TransactionId StartTime EndTime Power xyza123 2018.01.01 07:07:34 2018.01.01 07:34:08 70 hjker383 2018.01.01 10:21:00 2018.01.01 11:40:08 23My Goal is to assign a new Start- and EndTime which are set at 15 min values. Like so:
TransactionId StartTime New Starttime EndTime New EndTime Power xyza123 2018.01.01 07:07:34 2018.01.01 07:00:00 2018.01.01 07:34:08 2018.01.01 07:30:00 70 hjker383 2018.01.01 10:21:00 2018.01.01 10:30:00 2018.01.01 11:40:08 2018.01.01 11:45:00 23The old Timestamps can be deleted afterwards. However I don't want to aggregate them. So I guess
df.groupby(pd.Grouper(key="StartTime", freq="15min")).sum()
or
df.groupby(pd.Grouper(key="StartEndtime", freq="15min")).mean()
etc. is not an option.
Another idea I had was creating a dataframe with values between 2018.01.01 00:00:00
and 2018.01.01 23:45:00
. However I am not sure how to iterate true the two dataframes, to achieve my goal and if iteration true dataframes is a good idea in the first place.
ANSWER
Answered 2021-Apr-28 at 08:27You can use a function to convert a datetime to nearest 15 minute and then apply it to the column This function was inspired from this link:
QUESTION
I'd like to have a running year to date pct change column in my pandas dataframe:
Here is the dataframe:
...ANSWER
Answered 2021-Jun-12 at 14:49If I understand you well, you want the running percent change with respect to the last value of the previous year. It’s maybe not the most elegant, but you can explicitly build this last-value-of-previous-year series.
To start, you build a series with the date indices and years as values:
QUESTION
Lets say I have the following Time Series with an item:
...ANSWER
Answered 2021-Jun-12 at 00:36Try groupby size
on both pd.Grouper
and item
(use Anchored Offset to set Saturday to Saturday weekly):
QUESTION
I have a timeseries dataframe of rain values for every given hour.
This is the current dataframe:
print(assomption_rain_df.head(25))
ANSWER
Answered 2021-Jun-09 at 16:36You are looking for DataFrame.rolling
. It creates a rolling window of size n
that you can perform operations with.
You want
QUESTION
I am trying to aggregate a bunch of dictionaries, with string keys and lists of binary numbers as values, stored in a pandas dataframe. Like this:
Example dataframe that this problem occurs with:
...ANSWER
Answered 2021-Jun-09 at 09:46The issue is that merge_probe_trial_dicts
mutates the original list that is in df4
instead of creating a new one.
Just add .copy()
as below and you should be good.
QUESTION
I have a dataframe that is made up of hourly electricity price data. What I am trying to do is find a way to calculate the average of the n lowest price hourly periods in day. The data spans many years and aiming to get the average of the n lowest price periods for each day. Synthetic data can be created using the following:
...ANSWER
Answered 2021-Jun-07 at 12:43We can group the dataframe by Grouper
object with daily frequency then aggregate Price
using nsmallest
to obtain the n
smallest values, now calculate the mean
on level=0
to get the average of n
smallest values in a day
QUESTION
I have some hierarchical data from 2003 to 2011 which bottoms out into time series data which looks something like this:
...ANSWER
Answered 2021-Jun-07 at 09:06I have created synthetic data to test your approach and it worked fine. I then arbitrarily removed data points to see if the aggregation would fail with missing dates and it skips missing values from the time series, as displayed on the output immediately below. Therefore, I still don't understand why your output stops in 2005.
Output without resampling and interpolation:
QUESTION
I have a pandas dataframe the looks like the following:
...ANSWER
Answered 2021-Jun-01 at 10:49Convert val
to numeric first and then remove []
around 'lat', 'lon'
:
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
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Install Grouper
You can use Grouper 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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