MultiIndex.item() [source] return the first element of the underlying data as a python scalar

Series.put(*args, **kwargs) [source] Applies the put method to its values attribute if it has one. See also numpy.ndarray.put

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

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

MultiIndex.get_value(series, key) [source]

TimedeltaIndex.asi8

Panel4D.get_ftype_counts() [source] Return the counts of ftypes in this object.

Resampler.prod(_method='prod', *args, **kwargs) [source] Compute prod of group values See also pandas.Series.groupby, pandas.DataFrame.groupby, pandas.Panel.groupby

DataFrame.icol(i) [source] DEPRECATED. Use .iloc[:, i] instead

Panel4D.transpose(*args, **kwargs) [source] Permute the dimensions of the Panel Parameters: args : three positional arguments: each oneof {0, 1, 2, ?items?, ?major_axis?, ?minor_axis?} copy : boolean, default False Make a copy of the underlying data. Mixed-dtype data will always result in a copy Returns: y : same as input Examples >>> p.transpose(2, 0, 1) >>> p.transpose(2, 0, 1, copy=True)