pandleau

A quick and easy way to convert a Pandas DataFrame to a Tableau .tde or .hyper extract.

Getting Started

Prerequisites

If you want to output as a .tde format, you'll need to install TableauSDK directly from Tableau's site here.
If you want to output as a .hyper format, you'll need to install Extract API 2.0 directly from Tableau's site here.
Although Tableau's site claims Python 3 is not supported, this module has been tested to work fully functionally on Python 3.6.

Installing

Once installing TableauSDK is done, download this repository, navigate to your downloads file and run the following in cmd or terminal:

python -m setup.py install

You can also install pandleau using pip:

pip install pandleau

But note that this will throw a warning to install tableausdk using the above link in Prerequisites.

Example

I grabbed the following Brazil flights data off of kaggle for this example: https://www.kaggle.com/microtang/exploring-brazil-flights-data/data.

import pandas as pd
from pandleau import *

# Import the data
example_df = pd.read_csv(r'example/BrFlights2.csv', encoding = 'iso-8859-1')

# Format dates in pandas
example_df['Partida.Prevista'] = pd.to_datetime(example_df['Partida.Prevista'], format = '%Y-%m-%d')
example_df['Partida.Real'] = pd.to_datetime(example_df['Partida.Real'], format = '%Y-%m-%d')
example_df['Chegada.Prevista'] = pd.to_datetime(example_df['Chegada.Prevista'], format = '%Y-%m-%d')
example_df['Chegada.Real'] = pd.to_datetime(example_df['Chegada.Real'], format = '%Y-%m-%d')

# Set up a spatial column
example_df.loc[:, 'SpatialDest'] = example_df['LongDest'].apply( lambda x: "POINT (" + str( round(x, 6) ) ) + \
	example_df['LatDest'].apply( lambda x: " "+str( round(x, 6) ) + ")" )

# Change to pandleau object
df_tableau = pandleau(example_df)

# Define spatial column
df_tableau.set_spatial('SpatialDest', indicator=True)

# Write .tde or .hyper Extract!
df_tableau.to_tableau('test.hyper', add_index=False)

Tableau Server/Online Automation

Eric Chan (erickhchan) wrote a really cool blog post on using Python to blend and clean data before pushing it to Tableau Online (which is a SaaS version of Tableau Server). This is a great way to learn how to automate the data refresh process with Tableau Server Client and Pandleau. Check out his blog post here: https://www.erickhchan.com/data/2019/03/18/python-tableau-server.html

Authors

Benjamin Wiley - jamin4lyfe
Zhirui(Jerry) Wang - zhiruiwang
Pointy Shiny Burning - PointyShinyBurning
Aaron Wiegel - aawiegel
Ricky Schools - rickyschools
Kene Udeh - kudeh
Harrison - harrison-h

Related Project

RTableau Convert R data.frame to Tableau Extract using pandleau

License

This project is licensed under the MIT License - see the LICENSE.md file for details

bwiley1/pandleau