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python merge 資料合併
1：只有乙個key
import pandas as pd
left = pd.dataframe()
right = pd.dataframe()
#以某個條件作為合併媒介
res = pd.merge(left,right,on='key')
a b key c d
0 a0 b0 k0 c0 d0
1 a1 b1 k1 c1 d1
2 a2 b2 k2 c2 d2
3 a3 b3 k3 c3 d3
2：2個key
import pandas as pd
left = pd.dataframe()
right = pd.dataframe()
res1 = pd.merge(left,right,on=['key1','key2'],how='inner')
how=『inner』 輸出結果：
a b key1 key2 c d
0 a0 b0 k0 k0 c0 d0
1 a2 b2 k1 k0 c1 d1
2 a2 b2 k1 k0 c2 d2
2.2 outer 連線
res2 = pd.merge(left,right,on=['key1','key2'],how='outer')a b key1 key2 c d
0 a0 b0 k0 k0 c0 d0
1 a1 b1 k0 k1 nan nan
2 a2 b2 k1 k0 c1 d1
3 a2 b2 k1 k0 c2 d2
4 a3 b3 k2 k1 nan nan
5 nan nan k2 k0 c3 d3
2.3 left 連線
res3 = pd.merge(left,right,on=['key1','key2'],how='left')a b key1 key2 c d
0 a0 b0 k0 k0 c0 d0
1 a1 b1 k0 k1 nan nan
2 a2 b2 k1 k0 c1 d1
3 a2 b2 k1 k0 c2 d2
4 a3 b3 k2 k1 nan nan
2.4 right 連線
res4 = pd.merge(left,right,on=['key1','key2'],how='right')a b key1 key2 c d
0 a0 b0 k0 k0 c0 d0
1 a2 b2 k1 k0 c1 d1
2 a2 b2 k1 k0 c2 d2
3 nan nan k2 k0 c3 d3
3：indicator 引數
df1 = pd.dataframe()
df2 = pd.dataframe()
res = pd.merge(df1,df2,on='col1',how='outer',indicator=true)#預設false
col1 col_left col_right _merge
0 0 a nan left_only
1 1 b 2.0 both
2 2 nan 2.0 right_only
3 2 nan 2.0 right_only
修改列名字
res2 = pd.merge(df1,df2,on='col1',how='outer',indicator='indicator_name')col1 col_left col_right indicator_name
0 0 a nan left_only
1 1 b 2.0 both
2 2 nan 2.0 right_only
3 2 nan 2.0 right_only
4：merged by index
left = pd.dataframe(,
index = ['k0','k1','k2'])
right = pd.dataframe(,
index = ['k0','k2','k3'])
res1 = pd.merge(left,right,left_index=true,right_index=true,how='outer')a b c d
k0 a0 b0 c0 d0
k1 a1 b1 nan nan
k2 a2 b2 c2 d2
k3 nan nan c3 d3
res2 = pd.merge(left,right,left_index=true,right_index=true,how='inner')a b c d
k0 a0 b0 c0 d0
k2 a2 b2 c2 d2
boys = pd.dataframe()
girls = pd.dataframe()
res = pd.merge(boys,girls,on='k',suffixes=['_boys','_girls'],how='outer')
age_boys k age_girls
0 1.0 k0 4.0
1 1.0 k0 5.0
2 2.0 k1 nan
3 3.0 k2 nan
4 nan k3 6.0
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