pandas的一些应用

1.DataFrame.sub(other, axis='columns', level=None, fill_value=None)(dataframe相减)

Subtraction of dataframe and other, element-wise (binary operator sub).

Equivalent to dataframe - other, but with support to substitute a fill_value for missing data in one of the inputs.

2.DataFrame.apply(func, axis=0, broadcast=False, raw=False, reduce=None, args=(), **kwds)

Applies function along input axis of DataFrame.

Objects passed to functions are Series objects having index either the DataFrame’s index (axis=0) or the columns (axis=1). 

Return type depends on whether passed function aggregates, or the reduce argument if the DataFrame is empty.

3.DataFrame.sort_index(axis=0, by=None, ascending=True, inplace=False, kind='quicksort')

Sort DataFrame either by labels (along either axis) or by the values in a column

4.DataFrame.sort_values(by, axis=0, ascending=True, inplace=False, kind='quicksort', na_position='last') Sort by the values along either axis

5.DataFrame.cumsum(axis=None, dtype=None, out=None, skipna=True, **kwargs)

Return cumulative sum over requested axis.

6.DataFrame.dropna(axis=0, how='any', thresh=None, subset=None, inplace=False) Return object with labels on given axis omitted where alternately any or all of the data are missing

7.DataFrame.map

Like values in a Series, axis labels can be similarly transformed by a function or mapping of some form to produce new, differently labeled objects. You can also modify the axes in-place without creating a new data structure. Here’s a simple example:

7.DataFrame.sample(n=None, frac=None, replace=False, weights=None, random_state=None, axis=None)     Returns a random sample of items from an axis of object.


8. dummy variables

这里用df[['data1']].join（dummies）相当于直接删除了key这一列，把想要的直接加在后面了。

9.多维DataFrame的拆解

10.DataFrame. join ( other,  on=None,  how='left',  lsuffix='',  rsuffix='',  sort=False ) Join columns with other DataFrame either on index or on a key column. Efficiently Join multiple DataFrame objects by index at once by passing a list.

11.groupby中使用函数