Pandas 在 DataFrame 中插入行小计答案

【问题标题】：Pandas Insert Row Subtotal in a DataFramePandas 在 DataFrame 中插入行小计
【发布时间】：2018-03-07 21:32:37
【问题描述】：

enter image description here目标：我有一个 pandas 数据框，如下所示，其中包含多个列，并希望获取几列的小计并在 Placement# Name 处写入“Total”。

数据帧： enter image description here

我的尝试：

**adsize_sales_second_table.loc["Grand Total"] = pd.Series(adsize_sales_second_table.loc
                                                             [:, ["Delivered Impressions",
                                                                  "Clicks",
                                                                  "Conversion", "Spend"]].sum(),
                                                    index=["Delivered Impressions", "Clicks", "Conversion", "Spend"]**
                                                             )

这是最后添加一行，无法计算填充小计： enter image description here

预期输出： 我本来希望输出如下 enter image description here

查看修改后的代码：

  adsize_sales_data = adsize_sales_second_table.loc[:, ["Placement# Name", "Adsize", "Delivered Impressions", "Clicks",
                                                              "CTR", "Conversion", "Conversion Rate", "Spend", "eCPA"]]


        cols = ["Delivered Impressions", "Clicks", "Conversion", "Spend"]

        adsize_sales_data['Placement# Name'] = adsize_sales_data['Placement# Name'].ffill()
        grand = adsize_sales_data[cols].sum()
        grand.loc['Placement# Name'] = 'Grand total'

        adsize_sales_data_new = adsize_sales_data.groupby('Placement# Name')[cols].sum()

        adsize_sales_data_new.index = adsize_sales_data.index.astype(str)+'____'

        adsize_sales_data = (pd.concat([adsize_sales_data.set_index('Placement# Name'), adsize_sales_data_new], keys=('a', 'b')).sort_index(level=1).reset_index())

        adsize_sales_data['Placement# Name'] = np.where(adsize_sales_data ['level_0'] == 'a', adsize_sales_data['Placement# Name'], 'Total')

        adsize_sales_data = adsize_sales_data.drop('level_0', axis=1)

        adsize_sales_data.loc[len(adsize_sales_data.index)] = grand

        print (adsize_sales_data)

它现在给出值错误。enter image description here

【问题讨论】：

标签： python pandas data-science xlsxwriter

【解决方案1】：

用途：

#specify columns to sum
cols = ["Delivered Impressions", "Clicks", "Conversion", "Spend"]
#replace NaNs by forward filling
df['Placement# Name'] = df['Placement# Name'].ffill()
#count grand total
grand = df[cols].sum()
grand.loc['Placement# Name'] = 'Grand total'
print (grand)

#get subtotal by aggregation sum 
df1 = df.groupby('Placement# Name')[cols].sum()
#change sum for correct order
df1.index = df1.index + '____'
#join to original, sort by second level of MultiIndex
df = (pd.concat([df.set_index('Placement# Name'), df1], keys=('a', 'b'))
        .sort_index(level=1)
        .reset_index())

#change values to total
df['Placement# Name'] = np.where(df['level_0'] == 'a', df['Placement# Name'], 'Total')
#remove column
df = df.drop('level_0', axis=1)
#add grand total
df.loc[len(df.index)] = grand

print (df)
                                      Placement# Name   Adsize          CTR  \
0   13.iab units (mobile only) + non-expanding adh...   320x50    0.0119683   
1                                               Total      NaN          NaN   
2   15.iab units (mobile only) + non-expanding adh...   320x50    0.0138741   
3   15.iab units (mobile only) + non-expanding adh...   768x90    0.0271041   
4                                               Total      NaN          NaN   
5                     18.iab units - desktop + mobile  160x600   0.00155927   
6                     18.iab units - desktop + mobile  300x250   0.00797965   
7                     18.iab units - desktop + mobile  300x600   0.00275059   
8                     18.iab units - desktop + mobile   728x90   0.00496391   
9                                               Total      NaN          NaN   
10  4.iab units (mobile only) + non-expanding adhe...   320x50    0.0141497   
11                                              Total      NaN          NaN   
12  5.iab units (mobile only) + non-expanding adhe...   320x50    0.0111654   
13  5.iab units (mobile only) + non-expanding adhe...   768x90    0.0253428   
14                                              Total      NaN          NaN   
15                     6.iab units - desktop + mobile  160x600  7.41895e-05   
16                     6.iab units - desktop + mobile  300x250     0.011838   
17                     6.iab units - desktop + mobile  300x600  0.000259538   
18                     6.iab units - desktop + mobile   728x90   0.00538178   
19                                              Total      NaN          NaN   
20                                        Grand total      NaN          NaN   

   Clicks Conversion Conversion Rate Delivered Impressions    Spend     eCPA  
0    1888          4     2.53566e-05                157750  1126.79  281.696  
1    1888          4             NaN                157750  1126.79      NaN  
2    2121         17     0.000111202                152875  1091.96  64.2332  
3     152          2     0.000356633                  5608  40.0571  20.0286  
4    2273         19             NaN                158483  1132.02      NaN  
5      37         21     0.000884993                 23729  132.204  6.29545  
6     684         58     0.000676637                 85718  477.572    8.234  
7      34         13      0.00105169                 12361  68.8684  5.29757  
8     403         80     0.000985392                 81186  452.322  5.65403  
9    1158        172             NaN                202994  1130.97      NaN  
10   3840         23     8.47511e-05                271383  1938.45  84.2804  
11   3840         23             NaN                271383  1938.45      NaN  
12   1127          4     3.96287e-05                100937  720.979  180.245  
13    183          0               0                  7221  51.5786        0  
14   1310          4             NaN                108158  772.557      NaN  
15      1          0               0                 13479  75.0973        0  
16    792          0               0                 66903  372.745        0  
17      1          0               0                  3853  21.4667        0  
18    266          0               0                 49426  275.373        0  
19   1060          0             NaN                133661  744.683      NaN  
20  11529        222             NaN           1.03243e+06  6845.46      NaN  

#if necessary write to file
df.to_excel('file.xlsx', index=False)

编辑1：

cols = ["Delivered Impressions", "Clicks", "Conversion", "Spend"]

df['Placement# Name'] = df['Placement# Name'].ffill()
grand = df[cols].sum()
grand.loc['Placement# Name'] = 'Grand total'
print (grand)

df1 = df.groupby('Placement# Name')[cols].sum()
df1.index = df1.index + '____'

#create empty DataFrame
df2 = pd.DataFrame(index=df1.index + '__')
df = pd.concat([df.set_index('Placement# Name'), df1, df2], keys=('a', 'b', 'c')).sort_index(level=1).reset_index()

#get output by 2 conditions
m1 = df['level_0'] == 'a'
m2 = df['level_0'] == 'c'
df['Placement# Name'] = np.select([m1, m2], [df['Placement# Name'], np.nan], default='Total')
df = df.drop('level_0', axis=1)
df.loc[len(df.index)] = grand

print (df)
0   13.iab units (mobile only) + non-expanding adh...   320x50    0.0119683   
1                                               Total      NaN          NaN   
2                                                 NaN      NaN          NaN   
3   15.iab units (mobile only) + non-expanding adh...   320x50    0.0138741   
4   15.iab units (mobile only) + non-expanding adh...   768x90    0.0271041   
5                                               Total      NaN          NaN   
6                                                 NaN      NaN          NaN   
7                     18.iab units - desktop + mobile  160x600   0.00155927   
8                     18.iab units - desktop + mobile  300x250   0.00797965   
9                     18.iab units - desktop + mobile  300x600   0.00275059   
10                    18.iab units - desktop + mobile   728x90   0.00496391   
11                                              Total      NaN          NaN   
12                                                NaN      NaN          NaN   
13  4.iab units (mobile only) + non-expanding adhe...   320x50    0.0141497   
14                                              Total      NaN          NaN   
15                                                NaN      NaN          NaN   
16  5.iab units (mobile only) + non-expanding adhe...   320x50    0.0111654   
17  5.iab units (mobile only) + non-expanding adhe...   768x90    0.0253428   
18                                              Total      NaN          NaN   
19                                                NaN      NaN          NaN   
20                     6.iab units - desktop + mobile  160x600  7.41895e-05   
21                     6.iab units - desktop + mobile  300x250     0.011838   
22                     6.iab units - desktop + mobile  300x600  0.000259538   
23                     6.iab units - desktop + mobile   728x90   0.00538178   
24                                              Total      NaN          NaN   
25                                                NaN      NaN          NaN   
26                                        Grand total      NaN          NaN   

   Clicks Conversion Conversion Rate Delivered Impressions    Spend     eCPA  
0    1888          4     2.53566e-05                157750  1126.79  281.696  
1    1888          4             NaN                157750  1126.79      NaN  
2     NaN        NaN             NaN                   NaN      NaN      NaN  
3    2121         17     0.000111202                152875  1091.96  64.2332  
4     152          2     0.000356633                  5608  40.0571  20.0286  
5    2273         19             NaN                158483  1132.02      NaN  
6     NaN        NaN             NaN                   NaN      NaN      NaN  
7      37         21     0.000884993                 23729  132.204  6.29545  
8     684         58     0.000676637                 85718  477.572    8.234  
9      34         13      0.00105169                 12361  68.8684  5.29757  
10    403         80     0.000985392                 81186  452.322  5.65403  
11   1158        172             NaN                202994  1130.97      NaN  
12    NaN        NaN             NaN                   NaN      NaN      NaN  
13   3840         23     8.47511e-05                271383  1938.45  84.2804  
14   3840         23             NaN                271383  1938.45      NaN  
15    NaN        NaN             NaN                   NaN      NaN      NaN  
16   1127          4     3.96287e-05                100937  720.979  180.245  
17    183          0               0                  7221  51.5786        0  
18   1310          4             NaN                108158  772.557      NaN  
19    NaN        NaN             NaN                   NaN      NaN      NaN  
20      1          0               0                 13479  75.0973        0  
21    792          0               0                 66903  372.745        0  
22      1          0               0                  3853  21.4667        0  
23    266          0               0                 49426  275.373        0  
24   1060          0             NaN                133661  744.683      NaN  
25    NaN        NaN             NaN                   NaN      NaN      NaN  
26  11529        222             NaN           1.03243e+06  6845.46      NaN

【讨论】：

感谢您的工作，但是，它看起来有点棘手。如果数据框看起来像附加的屏幕截图并在同一个文件上获得输出怎么办？是否易于检查？查看修改
@abhilashmishra - 如果想使用 pandas，我没有更好的解决方案，抱歉。另一个数据框有问题吗？你能解释一下什么是问题吗？
在这一行 adsize_sales_data_new.index=adsize_sales_data.index+'____' 上给出类型错误“TypeError: unsupported operand type(s) for +: 'long' and 'str'”
然后使用adsize_sales_data_new.index=adsize_sales_data.index.astype(str)+'____'
知道了。谢谢一百万