pandas 之 concat

本文摘自：http://pandas.pydata.org/pandas-docs/stable/merging.html

前提：

ide：

liuqian@ubuntu:~$ ipython 

准備：

In [1]: import pandas as pd

In [2]: df1 = pd.DataFrame({'A': ['A0', 'A1', 'A2', 'A3'],  ...: 'B': ['B0', 'B1', 'B2', 'B3'],  ...:  'C': ['C0', 'C1', 'C2', 'C3'],  ...:  'D': ['D0', 'D1', 'D2', 'D3']},  ...:  index=[0, 1, 2, 3])  ...:  In [3]: df2 = pd.DataFrame({'A': ['A4', 'A5', 'A6', 'A7'],  ...:  'B': ['B4', 'B5', 'B6', 'B7'],  ...:  'C': ['C4', 'C5', 'C6', 'C7'],  ...:  'D': ['D4', 'D5', 'D6', 'D7']},  ...:  index=[4, 5, 6, 7])  ...:  In [4]: df3 = pd.DataFrame({'A': ['A8', 'A9', 'A10', 'A11'],  ...:  'B': ['B8', 'B9', 'B10', 'B11'],  ...:  'C': ['C8', 'C9', 'C10', 'C11'],  ...:  'D': ['D8', 'D9', 'D10', 'D11']},  ...:  index=[8, 9, 10, 11]) ...: In [4]: frames = [df1, df2, df3] In [5]: result = pd.concat(frames), 11])  ...:  In [5]: frames = [df1, df2, df3] # 不要忘了 

, 11]) ...: In [4]: frames = [df1, df2, df3] In [5]: result = pd.concat(frames)

語法：

pd.concat(objs, axis=0, join='outer', join_axes=None, ignore_index=False, keys=None, levels=None, names=None, verify_integrity=False, copy=True)

實例1：

In [6]: result = pd.concat(frames)    # 等價於 result = df1.append([df2, df3])

In [7]: result = pd.concat(frames, axis=1)

實例2：

In [8]: result = pd.concat(frames, keys=['x', 'y', 'z'])

In [9]: result = pd.concat(frames, keys=['x', 'y', 'z'], axis=1)

實例3：

In [10]: df4 = pd.DataFrame({'B': ['B2', 'B3', 'B6', 'B7'],
   ...:  'D': ['D2', 'D3', 'D6', 'D7'],
   ...:  'F': ['F2', 'F3', 'F6', 'F7']},
   ...:  index=[2, 3, 6, 7])
   ...: 

In [11]: result = pd.concat([df1, df4], axis=1, join='inner')

In [12]: result = pd.concat([df1, df4], join='inner')

實例4：

In [13]: result = pd.concat([df1, df4], axis=1, join_axes=[df1.index])

In [14]: result = pd.concat([df1, df4],  join_axes=[df1.columns])

實例5：

In [15]: result = pd.concat([df1, df4], ignore_index=True)   # 等價於 df1.append(df4, ignore_index=True)

In [16]: result = pd.concat([df1, df4], axis=1, ignore_index=True)

 

總結：

 1， axis=0, 對行操作    axis=1， 對列操作
 2. join='outer', 連接各個數據 join='inner',只取各個數據的公共部分
 3. join_axes=[df1.index], 保留與df1的行標簽一樣的數據，配合axis=1一起用 
 join_axes=[df1.columns]，保留與df1的列標簽一樣的數據，不要添加axis=1
 4. ignore_index=False, 保留原索引 ignore_index=True,忽略原索引並生成新索引
 5. keys=['x', 'y', 'z'] 對組成的每個df重新添加個索引