NOTICE: pandas-td is no longer maintained and planned to be archived on GitHub on April 17, 2020. Use pytd instead.

See a guide to replacing pandas-td with pytd and its official documentation for more information.

Pandas-TD [deprecated]

Documentation

• Tutorial (https://github.com/treasure-data/pandas-td/blob/master/doc/tutorial.ipynb)
• Magic functions (https://github.com/treasure-data/pandas-td/blob/master/doc/magic.ipynb)

Install

You can install the releases from PyPI:

$ pip install pandas-td

On Mac OS X, you can install Pandas and Jupyter as follows:

# Use Homebrew to install Python 3.x
$ brew install python3

# Install pandas, pandas-td, and jupyter
$ pip3 install pandas pandas-td jupyter

# Set API key and start a session
$ export TD_API_KEY=...
$ jupyter notebook

Examples

import pandas_td as td

# Initialize query engine
engine = td.create_engine('presto:sample_datasets')

# Read Treasure Data query into a DataFrame.
df = td.read_td('select * from www_access', engine)

# Read Treasure Data table into a DataFrame.
df = td.read_td_table('nasdaq', engine, limit=10000)

# Write a DataFrame to a Treasure Data table.
con = td.connect()
td.to_td(df, 'my_db.test_table', con, if_exists='replace', index=False)

Magic functions (experimental):

In [1]: %%load_ext pandas_td.ipython

# Use database
In [2]: %td_use sample_datasets

# Run query
In [3]: %%td_presto
   ...: select * from www_access

License

Apache Software License, Version 2.0