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DOC: Use a standard header for all rst files
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‎doc/source/10min.rst‎

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.. _10min:
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.. currentmodule:: pandas
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.. ipython:: python
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:suppress:
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import os
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import numpy as np
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import pandas as pd
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np.random.seed(123456)
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np.set_printoptions(precision=4, suppress=True)
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pd.options.display.max_rows = 15
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# portions of this were borrowed from the
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# Pandas cheatsheet
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# created during the PyData Workshop-Sprint 2012
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# Hannah Chen, Henry Chow, Eric Cox, Robert Mauriello
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{{ header }}
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********************
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10 Minutes to pandas

‎doc/source/advanced.rst‎

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.. _advanced:
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.. currentmodule:: pandas
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.. ipython:: python
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:suppress:
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import numpy as np
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import pandas as pd
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np.random.seed(123456)
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np.set_printoptions(precision=4, suppress=True)
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pd.options.display.max_rows = 15
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{{ header }}
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******************************
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MultiIndex / Advanced Indexing

‎doc/source/basics.rst‎

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.. currentmodule:: pandas
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.. ipython:: python
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:suppress:
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import numpy as np
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import pandas as pd
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np.set_printoptions(precision=4, suppress=True)
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pd.options.display.max_rows = 15
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{{ header }}
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==============================
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Essential Basic Functionality
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==============================

‎doc/source/categorical.rst‎

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.. _categorical:
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.. currentmodule:: pandas
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.. ipython:: python
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:suppress:
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import numpy as np
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import pandas as pd
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np.random.seed(123456)
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np.set_printoptions(precision=4, suppress=True)
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pd.options.display.max_rows = 15
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{{ header }}
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****************
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Categorical Data

‎doc/source/comparison_with_r.rst‎

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.. currentmodule:: pandas
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.. _compare_with_r:
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.. ipython:: python
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:suppress:
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import pandas as pd
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import numpy as np
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pd.options.display.max_rows = 15
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{{ header }}
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Comparison with R / R libraries
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*******************************

‎doc/source/computation.rst‎

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.. currentmodule:: pandas
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.. ipython:: python
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:suppress:
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import numpy as np
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import matplotlib.pyplot as plt
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import pandas as pd
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np.random.seed(123456)
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np.set_printoptions(precision=4, suppress=True)
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pd.options.display.max_rows = 15
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plt.close('all')
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.. _computation:
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{{ header }}
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Computational tools
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===================
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‎doc/source/conf.py‎

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}
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common_imports = """\
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header = """\
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.. currentmodule:: pandas
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.. ipython:: python
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:suppress:
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import csv
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from datetime import datetime, timedelta
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import functools
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import glob
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import itertools
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import os
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import numpy as np
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from pandas import *
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import pandas as pd
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from pandas.compat import StringIO, BytesIO
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import matplotlib
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import matplotlib.pyplot as plt
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randn = np.random.randn
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np.random.seed(123456)
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np.set_printoptions(precision=4, suppress=True)
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options.display.max_rows = 15
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from pandas.compat import StringIO
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pd.options.display.max_rows = 15
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plt.close('all')
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"""
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html_context = {
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'redirects': {old: new for old, new in moved_api_pages},
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'common_imports': common_imports,
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'header': header
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}
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# If false, no module index is generated.

‎doc/source/contributing.rst‎

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import warnings
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def old_func():
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"""Summary of the function.
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new_func()
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def new_func():
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pass
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.. code-block:: python
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df = pd.DataFrame()
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import pandas.util.testing as tm
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df = pd.DataFrame()
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with tm.assert_produces_warning(FutureWarning):
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df.some_operation()
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‎doc/source/cookbook.rst‎

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.. _cookbook:
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.. currentmodule:: pandas
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.. ipython:: python
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:suppress:
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import datetime
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import functools
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import glob
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import itertools
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import os
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import numpy as np
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import pandas as pd
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from pandas.compat import StringIO
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np.random.seed(123456)
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np.set_printoptions(precision=4, suppress=True)
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pd.options.display.max_rows = 15
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{{ header }}
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Cookbook
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s.max() - s
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s - datetime.datetime(2011, 1, 1, 3, 5)
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s - datetime(2011, 1, 1, 3, 5)
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s + datetime.timedelta(minutes=5)
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s + timedelta(minutes=5)
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datetime.datetime(2011, 1, 1, 3, 5) - s
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datetime(2011, 1, 1, 3, 5) - s
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datetime.timedelta(minutes=5) + s
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timedelta(minutes=5) + s
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`Adding and subtracting deltas and dates
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<http://stackoverflow.com/questions/16385785/add-days-to-dates-in-dataframe>`__
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deltas = pd.Series([datetime.timedelta(days=i) for i in range(3)])
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deltas = pd.Series([timedelta(days=i) for i in range(3)])
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df = pd.DataFrame({'A': s, 'B': deltas})
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df

‎doc/source/dsintro.rst‎

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.. currentmodule:: pandas
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.. ipython:: python
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:suppress:
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import numpy as np
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np.set_printoptions(precision=4, suppress=True)
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import pandas as pd
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pd.set_option('display.precision', 4, 'display.max_columns', 8)
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pd.options.display.max_rows = 15
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import matplotlib
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# matplotlib.style.use('default')
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import matplotlib.pyplot as plt
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plt.close('all')
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{{ header }}
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************************
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Intro to Data Structures
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************************

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