This is a guide to many pandas tutorials, geared mainly for new users. Internal Guides pandas own 10 Minutes to pandas More complex recipes are in the Cookbook pandas Cookbook The goal of this cookbook (by Julia Evans) is to give you some concrete examples for getting started with pandas. These are examples with real-world data, and all the bugs and weirdness that that entails. Here are links to the v0.1 release. For an up-to-date table of contents, see the pandas-cookbook GitHub repository

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

DatetimeIndex.values return the underlying data as an ndarray

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

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

MultiIndex.get_value(series, key) [source]

DataFrame.to_records(index=True, convert_datetime64=True) [source] Convert DataFrame to record array. Index will be put in the ?index? field of the record array if requested Parameters: index : boolean, default True Include index in resulting record array, stored in ?index? field convert_datetime64 : boolean, default True Whether to convert the index to datetime.datetime if it is a DatetimeIndex Returns: y : recarray

DataFrameGroupBy.corrwith(other, axis=0, drop=False) Compute pairwise correlation between rows or columns of two DataFrame objects. Parameters: other : DataFrame axis : {0 or ?index?, 1 or ?columns?}, default 0 0 or ?index? to compute column-wise, 1 or ?columns? for row-wise drop : boolean, default False Drop missing indices from result, default returns union of all Returns: correls : Series