Python?Pandas怎么修改表格數據類型DataFrame列的順序

本篇內容主要講解“Python Pandas怎么修改表格數據類型DataFrame列的順序”，感興趣的朋友不妨來看看。本文介紹的方法操作簡單快捷，實用性強。下面就讓小編來帶大家學習“Python Pandas怎么修改表格數據類型DataFrame列的順序”吧!

一、修改表格數據類型 DataFrame 列的順序

1.2創建 python 文件

import numpy as np
import pandas as pd

np.random.seed(66)
df = pd.DataFrame(np.random.rand(10, 4), columns=list('ABCD'))
print(df)
df = df[["D", "A", "B", "C"]]
print(df)

1.3運行結果 

          A         B         C         D
0  0.154288  0.133700  0.362685  0.679109
1  0.194450  0.251210  0.758416  0.557619
2  0.514803  0.467800  0.087176  0.829095
3  0.298641  0.031346  0.678006  0.903489
4  0.514451  0.539105  0.664328  0.634057
5  0.353419  0.026643  0.165290  0.879319
6  0.067820  0.369086  0.115501  0.096294
7  0.083770  0.086927  0.022256  0.771043
8  0.049213  0.465223  0.941233  0.216512
9  0.361318  0.031319  0.304045  0.188268
          D         A         B         C
0  0.679109  0.154288  0.133700  0.362685
1  0.557619  0.194450  0.251210  0.758416
2  0.829095  0.514803  0.467800  0.087176
3  0.903489  0.298641  0.031346  0.678006
4  0.634057  0.514451  0.539105  0.664328
5  0.879319  0.353419  0.026643  0.165290
6  0.096294  0.067820  0.369086  0.115501
7  0.771043  0.083770  0.086927  0.022256
8  0.216512  0.049213  0.465223  0.941233
9  0.188268  0.361318  0.031319  0.304045

二、Pandas 如何統計某個數據列的空值個數

2.2創建 python 文件

"""
對如下DF，設置兩個單元格的值
·使用iloc 設置(3,B)的值是nan
·使用loc設置(8,D)的值是nan
"""
import numpy as np
import pandas as pd
np.random.seed(66)
df = pd.DataFrame(np.random.rand(10, 4), columns=list('ABCD'))
df.iloc[3, 1] = np.nan
df.loc[8, 'D'] = np.nan
print(df)
print(df.isnull().sum())

2.3運行結果

          A         B         C         D
0  0.154288  0.133700  0.362685  0.679109
1  0.194450  0.251210  0.758416  0.557619
2  0.514803  0.467800  0.087176  0.829095
3  0.298641       NaN  0.678006  0.903489
4  0.514451  0.539105  0.664328  0.634057
5  0.353419  0.026643  0.165290  0.879319
6  0.067820  0.369086  0.115501  0.096294
7  0.083770  0.086927  0.022256  0.771043
8  0.049213  0.465223  0.941233       NaN
9  0.361318  0.031319  0.304045  0.188268
A    0
B    1
C    0
D    1
dtype: int64

三、Pandas如何移除包含空值的行

3.2創建 python 文件

"""
對如下DF，設置兩個單元格的值
·使用iloc 設置(3,B)的值是nan
·使用loc設置(8,D)的值是nan
"""
import numpy as np
import pandas as pd
 
np.random.seed(66)
df = pd.DataFrame(np.random.rand(10, 4), columns=list('ABCD'))
df.iloc[3, 1] = np.nan
df.loc[8, 'D'] = np.nan
print(df)
df2 = df.dropna()
print(df2)

3.3運行結果

          A         B         C         D
0  0.154288  0.133700  0.362685  0.679109
1  0.194450  0.251210  0.758416  0.557619
2  0.514803  0.467800  0.087176  0.829095
3  0.298641       NaN  0.678006  0.903489
4  0.514451  0.539105  0.664328  0.634057
5  0.353419  0.026643  0.165290  0.879319
6  0.067820  0.369086  0.115501  0.096294
7  0.083770  0.086927  0.022256  0.771043
8  0.049213  0.465223  0.941233       NaN
9  0.361318  0.031319  0.304045  0.188268
          A         B         C         D
0  0.154288  0.133700  0.362685  0.679109
1  0.194450  0.251210  0.758416  0.557619
2  0.514803  0.467800  0.087176  0.829095
4  0.514451  0.539105  0.664328  0.634057
5  0.353419  0.026643  0.165290  0.879319
6  0.067820  0.369086  0.115501  0.096294
7  0.083770  0.086927  0.022256  0.771043
9  0.361318  0.031319  0.304045  0.188268

四、Pandas如何精確設置表格數據的單元格的值

4.2創建 python 文件

"""
對如下DF，設置兩個單元格的值
·使用iloc 設置(3,B)的值是nan
·使用loc設置(8,D)的值是nan
"""
import numpy as np
import pandas as pd
np.random.seed(66)
df = pd.DataFrame(np.random.rand(10, 4), columns=list('ABCD'))
print(df)
 
df.iloc[3, 1] = np.nan
df.loc[8, 'D'] = np.nan
 
print(df)

4.3運行結果 

          A         B         C         D
0  0.154288  0.133700  0.362685  0.679109
1  0.194450  0.251210  0.758416  0.557619
2  0.514803  0.467800  0.087176  0.829095
3  0.298641  0.031346  0.678006  0.903489
4  0.514451  0.539105  0.664328  0.634057
5  0.353419  0.026643  0.165290  0.879319
6  0.067820  0.369086  0.115501  0.096294
7  0.083770  0.086927  0.022256  0.771043
8  0.049213  0.465223  0.941233  0.216512
9  0.361318  0.031319  0.304045  0.188268
          A         B         C         D
0  0.154288  0.133700  0.362685  0.679109
1  0.194450  0.251210  0.758416  0.557619
2  0.514803  0.467800  0.087176  0.829095
3  0.298641       NaN  0.678006  0.903489
4  0.514451  0.539105  0.664328  0.634057
5  0.353419  0.026643  0.165290  0.879319
6  0.067820  0.369086  0.115501  0.096294
7  0.083770  0.086927  0.022256  0.771043
8  0.049213  0.465223  0.941233       NaN
9  0.361318  0.031319  0.304045  0.188268 

到此，相信大家對“Python Pandas怎么修改表格數據類型DataFrame列的順序”有了更深的了解，不妨來實際操作一番吧！這里是億速云網站，更多相關內容可以進入相關頻道進行查詢，關注我們，繼續學習！