如何跳过xls末尾的pandas数据帧中的行

Question

我有一个数据框：

                                                        Energy Supply Energy Supply per Capita  % Renewable
    Country                                                                                                
    Afghanistan                                          3.210000e+08                       10    78.669280
    Albania                                              1.020000e+08                       35   100.000000
    British Virgin Islands                               2.000000e+06                       85     0.000000
    ...      
    Aruba                                                1.200000e+07                      120    14.870690                                                     ...                      
    Excludes the overseas territories.                            NaN                      NaN          NaN
    Data exclude Hong Kong and Macao Special Admini...            NaN                      NaN          NaN
    Data on kerosene-type jet fuel include aviation...            NaN                      NaN          NaN
    For confidentiality reasons, data on coal and c...            NaN                      NaN          NaN
    Data exclude Greenland and the Danish Faroes.                 NaN                      NaN          NaN

我曾使用df = pd.read_excel(filelink, skiprows=16)在文件的最开头删除不需要的信息但是如何摆脱df末尾的“noize”信息呢？

我曾尝试将一个列表传递给skiprows，但它搞砸了结果。

Answer 1

您似乎需要read_excel中的参数skip_footer = 5：

  

skip_footer ：int，默认为0

     

最后的行跳过（0索引）

样品：

df = pd.read_excel('myfile.xlsx', skip_footer = 5)
print (df)
                  Country  Energy Supply  Energy Supply per Capita  \
0             Afghanistan    321000000.0                        10   
1                 Albania    102000000.0                        35   
2  British Virgin Islands      2000000.0                        85   
3                   Aruba     12000000.0                       120   

   % Renewable   
0      78.66928  
1     100.00000  
2       0.00000  
3      14.87069  

另一种解决方案是使用dropna删除某些列中所有NaN的所有行：

df = pd.read_excel('myfile.xlsx')

cols = ['Energy Supply','Energy Supply per Capita','% Renewable']
df = df.dropna(subset=cols, how='all')
print (df)
                  Country  Energy Supply  Energy Supply per Capita  \
0             Afghanistan    321000000.0                      10.0   
1                 Albania    102000000.0                      35.0   
2  British Virgin Islands      2000000.0                      85.0   
3                   Aruba     12000000.0                     120.0   

   % Renewable  
0     78.66928  
1    100.00000  
2      0.00000  
3     14.87069