pd.concat(objs, axis=0, join='outer', join_axes=none, ignore_index=false,keys=none, levels=none, names=none, verify_integrity=false)asix:需要合併連線的軸,0是行,1是列
join:連線的方式,inner內連線,outer外連線
其它不常用引數......
#建立兩個物件
ser_1 = pd.series(np.random.randint(0,5,5),index=np.arange(5))
print(ser_1)
ser_2 = pd.series(np.random.randint(5,10,5),index=np.arange(5))
print(ser_2)
'''0 1
1 0
2 4
3 0
4 4
dtype: int32
0 7
1 9
2 6
3 5
4 5
dtype: int32
'''#axis預設為0,是橫向連線,返回乙個series物件
ser = pd.concat([ser_1,ser_2])
print(ser)
'''0 1
1 0
2 4
3 0
4 4
0 7
1 9
2 6
3 5
4 5
dtype: int32
'''
ser_1 = pd.series(np.random.randint(0,10,5),index=range(5))
ser_2 = pd.series(np.random.randint(0,10,4),index=range(4))
ser_3 = pd.series(np.random.randint(0,10,3),index=range(3))
print(ser_1)
'''0 4
1 3
2 6
3 4
4 6
dtype: int32
'''print(ser_2)
'''0 8
1 9
2 9
3 5
dtype: int32
'''print(ser_3)
'''0 6
1 0
2 3
dtype: int32
'''ser = pd.concat([ser_1,ser_2,ser_3],axis=1,join='inner')
print(ser)
'''dtype: int32
0 1 2
0 4 8 6
1 3 9 0
2 6 9 3
'''
ser_1 = pd.series(np.random.randint(0,10,5),index=range(5))
ser_2 = pd.series(np.random.randint(0,10,4),index=range(4))
ser_3 = pd.series(np.random.randint(0,10,3),index=range(3))
print(ser_1)
'''0 2
1 7
2 6
3 7
4 3
dtype: int32
'''print(ser_2)
'''0 7
1 4
2 7
3 0
dtype: int32
'''print(ser_3)
'''0 3
1 3
2 5
dtype: int32
'''ser = pd.concat([ser_1,ser_2,ser_3],axis=1,join='outer')
print(ser)
#返回乙個dataframe物件,並且取並集,對應位置沒有資料自動填充nan
''' 0 1 2
0 2 7.0 3.0
1 7 4.0 3.0
2 6 7.0 5.0
3 7 0.0 nan
4 3 nan nan
'''
# 建立兩個dataframe物件
df_1 = pd.dataframe(np.random.randint(0,10,(3,2)),index=['a','b','c'],columns=['a','b'])
df_2 = pd.dataframe(np.random.randint(0,10,(2,2)),index=['a','b'],columns=['c','d'])
print(df_1)
''' a b
a 7 0
b 0 8
c 9 3
'''print(df_2)
''' c d
a 7 5
b 4 0
'''df = pd.concat([df_1,df_2],axis=0)
print(df)
''' a b c d
a 9.0 9.0 nan nan
b 0.0 3.0 nan nan
c 4.0 7.0 nan nan
a nan nan 1.0 3.0
b nan nan 2.0 8.0
'''
# 建立兩個dataframe物件
df_1 = pd.dataframe(np.random.randint(0,10,(3,2)),index=['a','b','c'],columns=['a','b'])
df_2 = pd.dataframe(np.random.randint(0,10,(2,2)),index=['a','b'],columns=['c','d'])
print(df_1)
''' a b
a 5 6
b 8 9
c 4 7
'''print(df_2)
''' c d
a 5 4
b 2 0
'''df = pd.concat([df_1,df_2],axis=1)
print(df)
''' a b c d
a 5 6 5.0 4.0
b 8 9 2.0 0.0
c 4 7 nan nan
'''
import numpy as np
import pandas as pd
arr_1 = np.random.randint(0,10,(3,4))
arr_2 = np.random.randint(0,10,(3,4))
print(arr_1)
'''[[1 8 7 9]
[7 5 5 3]
[0 7 5 7]]
'''print(arr_2)
'''[[8 8 2 9]
[5 9 5 8]
[3 1 6 5]]
'''# concatenate 函式 合併的時候有軸向
arr = np.concatenate([arr_1,arr_2],axis=0)
print(arr)
'''[[1 8 7 9]
[7 5 5 3]
[0 7 5 7]
[8 8 2 9]
[5 9 5 8]
[3 1 6 5]]
'''arr = np.concatenate([arr_1,arr_2],axis=1)
print(arr)
'''[[1 8 7 9 8 8 2 9]
[7 5 5 3 5 9 5 8]
[0 7 5 7 3 1 6 5]]
'''
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