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:\Alex\WorkLog\34-deeplearning\myWorks\TransferLearningExample\mofangTransferLearning\1.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:\Alex\WorkLog\34-deeplearning\myWorks\TransferLearningExample\mofangTransferLearning\1.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:\ProgramData\Anaconda3\lib\site-packages\pandas\core\frame.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

　　

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