代码
import pandas as pd
import numpy as np
dates = pd.date_range('20130101', periods=6)
df=pd.DataFrame(np.arange(24).reshape((6,4)),index=dates, columns=['A','B','C','D'])
# 行数，列数，赋值
df.iloc[0,1] = np.nan
df.iloc[1,2] = np.nan
# 以行丢掉
print('-1-')
print(df.dropna(axis=0))
# 有nan就丢 这是默认情况
print('-2-')
print(df.dropna(axis=0, how='any'))
# 全是nan再丢
print('-3-')
print(df.dropna(axis=0, how='all'))
# 填上
print('-4-')
print(df.fillna(value=0))
# 判断每个的结果
print('-5-')
print(df.isnull())
# 整体内是不是有null
print('-6-')
print(np.any(df.isnull()) == True)
# 读取保存数据 read_csv to_csv
df1 = pd.DataFrame(np.ones((3,4))*0,columns=['a','b','c','d'])
df2 = pd.DataFrame(np.ones((3,4))*1,columns=['a','b','c','d'])
df3 = pd.DataFrame(np.ones((3,4))*2,columns=['a','b','c','d'])
print('-7-')
print(df1)
print(df2)
print(df3)
# axis=0 竖向合并
res = pd.concat([df1,df2,df3], axis=0)
print('-8-')
print(res)
res = pd.concat([df1,df2,df3], axis=0, ignore_index=True)
print('-9-')
print(res)
df1 = pd.DataFrame(np.ones((3,4))*0,columns=['a','b','c','d'],index=[1,2,3])
df2 = pd.DataFrame(np.ones((3,4))*1,columns=['b','c','d','e'],index=[2,3,4])
print('-10-')
print(df1)
print(df2)
# 组合模式
res = pd.concat([df1,df2])
print('-11-')
print(res)
# defalut 并集
res = pd.concat([df1,df2], join='outer')
print('-12-')
print(res)
# 交集
res = pd.concat([df1,df2], join='inner')
print('-13-')
print(res)
res = pd.concat([df1,df2], join='inner', ignore_index=True)
print('-14-')
print(res)
# axis=1 左右合并 只考虑df1的index
res = pd.concat([df1,df2], axis=1,join_axes=[df1.index])
print('-15-')
print(res)
# axis=1 左右合并
res = pd.concat([df1,df2], axis=1)
print('-16-')
print(res)
df1 = pd.DataFrame(np.ones((3,4))*0,columns=['a','b','c','d'])
df2 = pd.DataFrame(np.ones((3,4))*1,columns=['a','b','c','d'])
df3 = pd.DataFrame(np.ones((3,4))*2,columns=['b','c','d','e'],index=[2,3,4])
res = df1.append(df2, ignore_index=True)
print('-17-')
print(res)
res = df1.append([df2, df3], ignore_index=True)
print('-18-')
print(res)
s1 = pd.Series([1,2,3,4], index=['a','b','c','d'])
res = df1.append(s1,ignore_index=True)
print('-19-')
print(res)
输出
-1-
A B C D
2013-01-03 8 9.0 10.0 11
2013-01-04 12 13.0 14.0 15
2013-01-05 16 17.0 18.0 19
2013-01-06 20 21.0 22.0 23
-2-
A B C D
2013-01-03 8 9.0 10.0 11
2013-01-04 12 13.0 14.0 15
2013-01-05 16 17.0 18.0 19
2013-01-06 20 21.0 22.0 23
-3-
A B C D
2013-01-01 0 NaN 2.0 3
2013-01-02 4 5.0 NaN 7
2013-01-03 8 9.0 10.0 11
2013-01-04 12 13.0 14.0 15
2013-01-05 16 17.0 18.0 19
2013-01-06 20 21.0 22.0 23
-4-
A B C D
2013-01-01 0 0.0 2.0 3
2013-01-02 4 5.0 0.0 7
2013-01-03 8 9.0 10.0 11
2013-01-04 12 13.0 14.0 15
2013-01-05 16 17.0 18.0 19
2013-01-06 20 21.0 22.0 23
-5-
A B C D
2013-01-01 False True False False
2013-01-02 False False True False
2013-01-03 False False False False
2013-01-04 False False False False
2013-01-05 False False False False
2013-01-06 False False False False
-6-
True
-7-
a b c d
0 0.0 0.0 0.0 0.0
1 0.0 0.0 0.0 0.0
2 0.0 0.0 0.0 0.0
a b c d
0 1.0 1.0 1.0 1.0
1 1.0 1.0 1.0 1.0
2 1.0 1.0 1.0 1.0
a b c d
0 2.0 2.0 2.0 2.0
1 2.0 2.0 2.0 2.0
2 2.0 2.0 2.0 2.0
-8-
a b c d
0 0.0 0.0 0.0 0.0
1 0.0 0.0 0.0 0.0
2 0.0 0.0 0.0 0.0
0 1.0 1.0 1.0 1.0
1 1.0 1.0 1.0 1.0
2 1.0 1.0 1.0 1.0
0 2.0 2.0 2.0 2.0
1 2.0 2.0 2.0 2.0
2 2.0 2.0 2.0 2.0
-9-
a b c d
0 0.0 0.0 0.0 0.0
1 0.0 0.0 0.0 0.0
2 0.0 0.0 0.0 0.0
3 1.0 1.0 1.0 1.0
4 1.0 1.0 1.0 1.0
5 1.0 1.0 1.0 1.0
6 2.0 2.0 2.0 2.0
7 2.0 2.0 2.0 2.0
8 2.0 2.0 2.0 2.0
-10-
a b c d
1 0.0 0.0 0.0 0.0
2 0.0 0.0 0.0 0.0
3 0.0 0.0 0.0 0.0
b c d e
2 1.0 1.0 1.0 1.0
3 1.0 1.0 1.0 1.0
4 1.0 1.0 1.0 1.0
d:AlexWorkLog34-deeplearningmyWorksTransferLearningExamplemofangTransferLearning1.py:62: FutureWarning: Sorting because non-concatenation axis is not aligned. A future version
of pandas will change to not sort by default.
To accept the future behavior, pass 'sort=True'.
To retain the current behavior and silence the warning, pass sort=False
res = pd.concat([df1,df2])
-11-
a b c d e
1 0.0 0.0 0.0 0.0 NaN
2 0.0 0.0 0.0 0.0 NaN
3 0.0 0.0 0.0 0.0 NaN
2 NaN 1.0 1.0 1.0 1.0
3 NaN 1.0 1.0 1.0 1.0
4 NaN 1.0 1.0 1.0 1.0
d:AlexWorkLog34-deeplearningmyWorksTransferLearningExamplemofangTransferLearning1.py:66: FutureWarning: Sorting because non-concatenation axis is not aligned. A future version
of pandas will change to not sort by default.
To accept the future behavior, pass 'sort=True'.
To retain the current behavior and silence the warning, pass sort=False
res = pd.concat([df1,df2], join='outer')
-12-
a b c d e
1 0.0 0.0 0.0 0.0 NaN
2 0.0 0.0 0.0 0.0 NaN
3 0.0 0.0 0.0 0.0 NaN
2 NaN 1.0 1.0 1.0 1.0
3 NaN 1.0 1.0 1.0 1.0
4 NaN 1.0 1.0 1.0 1.0
-13-
b c d
1 0.0 0.0 0.0
2 0.0 0.0 0.0
3 0.0 0.0 0.0
2 1.0 1.0 1.0
3 1.0 1.0 1.0
4 1.0 1.0 1.0
-14-
b c d
0 0.0 0.0 0.0
1 0.0 0.0 0.0
2 0.0 0.0 0.0
3 1.0 1.0 1.0
4 1.0 1.0 1.0
5 1.0 1.0 1.0
-15-
a b c d b c d e
1 0.0 0.0 0.0 0.0 NaN NaN NaN NaN
2 0.0 0.0 0.0 0.0 1.0 1.0 1.0 1.0
3 0.0 0.0 0.0 0.0 1.0 1.0 1.0 1.0
-16-
a b c d b c d e
1 0.0 0.0 0.0 0.0 NaN NaN NaN NaN
2 0.0 0.0 0.0 0.0 1.0 1.0 1.0 1.0
3 0.0 0.0 0.0 0.0 1.0 1.0 1.0 1.0
4 NaN NaN NaN NaN 1.0 1.0 1.0 1.0
-17-
a b c d
0 0.0 0.0 0.0 0.0
1 0.0 0.0 0.0 0.0
2 0.0 0.0 0.0 0.0
3 1.0 1.0 1.0 1.0
4 1.0 1.0 1.0 1.0
5 1.0 1.0 1.0 1.0
C:ProgramDataAnaconda3libsite-packagespandascoreframe.py:6201: FutureWarning: Sorting because non-concatenation axis
is not aligned. A future version
of pandas will change to not sort by default.
To accept the future behavior, pass 'sort=True'.
To retain the current behavior and silence the warning, pass sort=False
sort=sort)
-18-
a b c d e
0 0.0 0.0 0.0 0.0 NaN
1 0.0 0.0 0.0 0.0 NaN
2 0.0 0.0 0.0 0.0 NaN
3 1.0 1.0 1.0 1.0 NaN
4 1.0 1.0 1.0 1.0 NaN
5 1.0 1.0 1.0 1.0 NaN
6 NaN 2.0 2.0 2.0 2.0
7 NaN 2.0 2.0 2.0 2.0
8 NaN 2.0 2.0 2.0 2.0
-19-
a b c d
0 0.0 0.0 0.0 0.0
1 0.0 0.0 0.0 0.0
2 0.0 0.0 0.0 0.0
3 1.0 2.0 3.0 4.0