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

• 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.

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.

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)

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

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

RTableau Convert R data.frame to Tableau Extract using pandleau

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