python-pivottable | generate Pivot Tables base on arbitrary objects

by marplatense Python Version: Current License: MIT

X-Ray Key Features Code Snippets(10)Community Discussions Vulnerabilities Install Support

kandi X-RAY | python-pivottable Summary

python-pivottable is a Python library. python-pivottable has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can install using 'pip install python-pivottable' or download it from GitHub, PyPI.

A module that will help you to generate Pivot Tables base on arbitrary objects.

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Quality

Security

License

Reuse

Support

python-pivottable has a low active ecosystem.

It has 11 star(s) with 7 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

There are 2 open issues and 0 have been closed. On average issues are closed in 2428 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of python-pivottable is current.

Quality

python-pivottable has 0 bugs and 0 code smells.

Security

python-pivottable has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

python-pivottable code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

python-pivottable 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

python-pivottable releases are not available. You will need to build from source code and install.

Deployable package is available in PyPI.

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

python-pivottable saves you 286 person hours of effort in developing the same functionality from scratch.

It has 690 lines of code, 47 functions and 5 files.

It has medium code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

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

return the result as a dict
list of headers
Creates an attribute getter for an object .
getter for itemgetter
Resolve attr .
Compute the sum
Append a new value to the list .

Get all kandi verified functions for this library.

python-pivottable Key Features

No Key Features are available at this moment for python-pivottable.

python-pivottable Examples and Code Snippets

Resample DataFrame in Pandas PivotTable

Python

Lines of Code : 28

License : Strong Copyleft (CC BY-SA 4.0)

Copy

df1['created_date'] = pd.to_datetime(df1['created_date'], dayfirst=True)
df1['subscr_date'] = pd.to_datetime(df1['subscr_date'], dayfirst=True)

df1 = df1.groupby([
    pd.Grouper(freq='M', key='created_date'),
    pd.Grouper(freq='M', key

Dictionary of conditions to use with pandas in a loop

Python

Lines of Code : 2

License : Strong Copyleft (CC BY-SA 4.0)

Copy

filter = {"Q1": df1.columns, "Q2":df1['state']=='NJ', "Q3":df1['zipcode']=='07030'}

How to get a Google sheet ID which doesn’t exist yet?

Python

Lines of Code : 6

License : Strong Copyleft (CC BY-SA 4.0)

Copy

spreadsheet = {'properties': {'title': "Testing-01"}}
spreadsheet = ss_service.spreadsheets().create(body=spreadsheet,
                                            fields='spreadsheetId').execute()
ss_id = spreadsheet.get('spreadsheetId')
p

create new column with values from another column based on condition

Python

Lines of Code : 11

License : Strong Copyleft (CC BY-SA 4.0)

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df['g'] = df.groupby('FY').cumcount()
df2 = df[['FY','Value','g']].assign(FY = df['FY'].add(1))

df = df.merge(df2, on=['FY','g'], how='left', suffixes=('','_prev')).drop('g', axis=1)
print (df)
   A  B Value    FY Value_prev
0  1  5     a

How change dataset (like pivottable in excell)

Python

Lines of Code : 17

License : Strong Copyleft (CC BY-SA 4.0)

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df1 = df.pivot('ParamID','EquipmentID','SetValue')
df1['Difference'] = (df1['Line1'].replace(np.nan,0) - df1['Line2'].replace(np.nan,0))
df1

df1 = df.pivot('ParamID','EquipmentID','SetValue').reset_index()
df1['Dif

How change dataset (like pivottable in excell)

Python

Lines of Code : 18

License : Strong Copyleft (CC BY-SA 4.0)

Copy

pivot1 = (df.pivot_table(index='ParamID', 
                         columns='EquipmentID', 
                         values='SetValue', 
                         fill_value=0)
            .reset_index()
            .rename_axis(columns=Non

Pandas: Pivoting multiple tables into single and counting occurences

Python

Lines of Code : 18

License : Strong Copyleft (CC BY-SA 4.0)

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tables = [df1,df2] # if you want to make the keys dynamic, 
#tables = table_dict = dict(zip([f'table {i}' for i in range(1,len(tables) + 1)],tables))

df_new = (
    pd.concat(tables, axis=0, keys=["table1", "table2"])
    .set_index("week

Pandas PivotTable

Python

Lines of Code : 7

License : Strong Copyleft (CC BY-SA 4.0)

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pd.get_dummies(df,columns=['Sector', 'Country'], prefix='', prefix_sep='')

    SecId        Date  Aerospace  Banking  Utility  FRA  USA
0  184149  2019-12-31          0        0        1    0    1
1  184150  2019-1

Pandas PivotTable

Python

Lines of Code : 12

License : Strong Copyleft (CC BY-SA 4.0)

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SECTORS = df.Sector.unique()
df["Sector"] = df.Sector.astype(pd.Categorical(SECTORS))
COUNTRIES = df.Country.unique()
df["Country"] = df.Country.astype(pd.Categorical(COUNTRIES))

df2 = pd.get_dummies(data=df, columns=["Sector", "Country"]

How to Group by Date Field in a PivotTable using win32com.client

Python

Lines of Code : 3

License : Strong Copyleft (CC BY-SA 4.0)

Copy

cell = pivot_sheet.Range('B5')
cell.Group(Start=True, End=True, Periods=list([False, False, False, False, True, False, True]))

Community Discussions

No Community Discussions are available at this moment for python-pivottable.Refer to stack overflow page for discussions.

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

Vulnerabilities

No vulnerabilities reported

Install python-pivottable

You can install using 'pip install python-pivottable' or download it from GitHub, PyPI.
You can use python-pivottable 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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