MultiIndex.get_value(series, key) [source]

Resampler.ffill(limit=None) [source] Forward fill the values Parameters: limit : integer, optional limit of how many values to fill See also Series.fillna, DataFrame.fillna

Panel4D.sort_values(by, axis=0, ascending=True, inplace=False, kind='quicksort', na_position='last') [source]

DataFrame.axes Return a list with the row axis labels and column axis labels as the only members. They are returned in that order.

MultiIndex.sort_values(return_indexer=False, ascending=True) [source] Return sorted copy of Index

Here we discuss a lot of the essential functionality common to the pandas data structures. Here?s how to create some of the objects used in the examples from the previous section: In [1]: index = pd.date_range('1/1/2000', periods=8) In [2]: s = pd.Series(np.random.randn(5), index=['a', 'b', 'c', 'd', 'e']) In [3]: df = pd.DataFrame(np.random.randn(8, 3), index=index, ...: columns=['A', 'B', 'C']) ...: In [4]: wp = pd.Panel(np.random.randn(2, 5, 4), items=['Item1', '

Panel4D.ffill(axis=None, inplace=False, limit=None, downcast=None) [source] Synonym for NDFrame.fillna(method=?ffill?)

Series.dt.weekday The day of the week with Monday=0, Sunday=6

This is a short introduction to pandas, geared mainly for new users. You can see more complex recipes in the Cookbook Customarily, we import as follows: In [1]: import pandas as pd In [2]: import numpy as np In [3]: import matplotlib.pyplot as plt Object Creation See the Data Structure Intro section Creating a Series by passing a list of values, letting pandas create a default integer index: In [4]: s = pd.Series([1,3,5,np.nan,6,8]) In [5]: s Out[5]: 0 1.0 1 3.0 2 5.0 3 NaN 4

DatetimeIndex.values return the underlying data as an ndarray