pyjanitor | Clean APIs for data

by pyjanitor-devs Python Version: 0.27.0 License: MIT

X-Ray Key Features Code Snippets(6)Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | pyjanitor Summary

pyjanitor is a Python library typically used in Data Science, Pandas applications. pyjanitor has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has medium support. You can install using 'pip install pyjanitor' or download it from GitHub, PyPI.

Clean APIs for data cleaning. Python implementation of R package Janitor

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Quality

Security

License

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Support

pyjanitor has a medium active ecosystem.

It has 1149 star(s) with 160 fork(s). There are 19 watchers for this library.

There were 1 major release(s) in the last 12 months.

There are 105 open issues and 424 have been closed. On average issues are closed in 70 days. There are 7 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of pyjanitor is 0.27.0

Quality

pyjanitor has 0 bugs and 0 code smells.

Security

pyjanitor has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

pyjanitor code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

pyjanitor is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

pyjanitor releases are available to install and integrate.

Deployable package is available in PyPI.

Build file is available. You can build the component from source.

Top functions reviewed by kandi - BETA

kandi has reviewed pyjanitor and discovered the below as its top functions. This is intended to give you an instant insight into pyjanitor implemented functionality, and help decide if they suit your requirements.

Returns a pandas DataFrame containing all cells in the given path
Return a dataframe of xlsx rows
Check if value is of expected type
Convert an object to a dictionary
Read a sheet from a sheet
Rename column names
Stripunderscores
Change column name
Convert camel case to snake_case
Dispatches column selection
Select column names
Check if df_columns is string or categorical dtype
Read requirements file
Mark a function as deprecated
Rename keyword arguments
Generate a long description
Convert stock symbol
Check if the URL is connected to the internet
Get symbol name
Count the number of functions in a file
Return all submodules
Factorize columns
Check if a column is present in the dataframe

Get all kandi verified functions for this library.

pyjanitor Key Features

No Key Features are available at this moment for pyjanitor.

pyjanitor Examples and Code Snippets

Change pandas dataframe format from wide to long similar to pd.melt

Python

Lines of Code : 12

License : Strong Copyleft (CC BY-SA 4.0)

Copy

( df.pivot_longer(index=None, 
                  names_to=("id", "source", "panel"), 
                  names_pattern=[r"^id", r"^source", r"^panel"])
   .query("id != ''")
 )

    id source panel
0  123     de    nq
1  145     de    nq
3

Split row by two columns and keep other columns the same

Python

Lines of Code : 52

License : Strong Copyleft (CC BY-SA 4.0)

Copy

(df.pivot_longer(index = ['col1', 'col2', 'Unique_Col'], 
                 names_to = ['Name_new', 'Gender_new', 'Age_new'],  
                 names_pattern = ['Name', 'Gender', 'Age'],
                 sort_by_appearance = True)
)
 
  co

Wide date to long data conversion in Python Pandas using column names

Python

Lines of Code : 35

License : Strong Copyleft (CC BY-SA 4.0)

Copy

df.columns = ["_".join(entry.split("_")[::-1]) 
              if entry.endswith(("count", "date"))
              else entry
              for entry in df.columns]

pd.wide_to_long(df, 
                ["count", "dat

Merge pandas DataFrames by partial match in datetime column

Python

Lines of Code : 23

License : Strong Copyleft (CC BY-SA 4.0)

Copy

df_booking.rename(columns={'DepartureTime':'DepartureTime_booking', 'Destination':'Destination_booking'}, inplace=True)
df_booking = df_booking.merge(df_info, on='IDs')

df_actual.rename(columns={'DepartureTime':'DepartureTime_actual', 'De

How to check splitted values of a column without changing the dataframe?

Python

Lines of Code : 4

License : Strong Copyleft (CC BY-SA 4.0)

Copy

sep='-'
deconcat = df['MyCol'].str.split(sep, expand=True)
new_df=df.join(deconcat)

Preserve original column names

Python

Lines of Code : 4

License : Strong Copyleft (CC BY-SA 4.0)

Copy

df_dct = {'df': santandar_data, 'original_names': santandar_data.columns}

df_dct['df'] = df_dct['df'].clean_names(...)

Community Discussions

Trending Discussions on pyjanitor

Merge pandas DataFrames by partial match in datetime column

QUESTION

Merge pandas DataFrames by partial match in datetime column

Asked 2020-Feb-09 at 12:24

Hello good people of stackoverflow. I can't quite grasp the solution here, so please, help me out. Please, keep in mind that I'm quite a beginner at python, so please, keep it as simple as you can.

My company provides employees with transportation to and from work. There is a system in place that tracks when employee got on the bus and which bus the person got onto. Also we receive data from transportation company with information where and when employees were supposed to go as per planning(every employee books the spot in advance). Sometimes people don't book places, sometimes they get onto the wrong bus(not the route they booked) or at the wrong time. My goal is to find such people and provide a report.

Here is the sample of the data we receive from the transportation company

...

ANSWER

Answered 2020-Feb-09 at 12:24

You can do as follows.

In the code below, the first df is named as df_booking,the second df is named as df_actual & the SQL database as df_info.

Source https://stackoverflow.com/questions/60135792

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install pyjanitor

You can install using 'pip install pyjanitor' or download it from GitHub, PyPI.
You can use pyjanitor 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.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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