如何将带有 NaN 的合并 Excel 单元格读入 Pandas DataFrame

Question

我想将 Excel 工作表读入 Pandas DataFrame。但是，有合并的 Excel 单元格以及空行（完整/部分 NaN 填充），如下所示。澄清一下，John H. 已下订单购买从“保镖”到“红丸蓝调”的所有专辑。

当我将此 Excel 工作表读入 Pandas DataFrame 时，Excel 数据无法正确传输。 Pandas 将合并的单元格视为一个单元格。 DataFrame 如下所示：（注意：() 中的值是我想要的值）

请注意最后一行不包含合并单元格；它仅带有 Artist 列的值。

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编辑： 我确实尝试了以下方法来向前填充 NaN 值：(Pandas: Reading Excel with merged cells)

df.index = pd.Series(df.index).fillna(method='ffill')  

但是，NaN 值仍然存在。 我可以使用什么策略或方法来正确填充 DataFrame？ 是否有一种 Pandas 方法可以取消合并单元格并复制相应的内容？

Answer 1

您尝试的引用链接只需要转发填充 index 列。对于您的用例，您需要为 all 数据框列 fillna。因此，只需向前填充整个数据框：

df = pd.read_excel("Input.xlsx")
print(df)

#    Order_ID Customer_name            Album_Name           Artist  Quantity
# 0       NaN           NaN            RadioShake              NaN       NaN
# 1       1.0       John H.         The Bodyguard  Whitney Houston       2.0
# 2       NaN           NaN              Lemonade          Beyonce       1.0
# 3       NaN           NaN  The Thrill Of It All        Sam Smith       2.0
# 4       NaN           NaN              Thriller  Michael Jackson      11.0
# 5       NaN           NaN                Divide       Ed Sheeran       4.0
# 6       NaN           NaN            Reputation     Taylor Swift       3.0
# 7       NaN           NaN        Red Pill Blues         Maroon 5       5.0

df = df.fillna(method='ffill')
print(df)

#    Order_ID Customer_name            Album_Name           Artist  Quantity
# 0       NaN           NaN            RadioShake              NaN       NaN
# 1       1.0       John H.         The Bodyguard  Whitney Houston       2.0
# 2       1.0       John H.              Lemonade          Beyonce       1.0
# 3       1.0       John H.  The Thrill Of It All        Sam Smith       2.0
# 4       1.0       John H.              Thriller  Michael Jackson      11.0
# 5       1.0       John H.                Divide       Ed Sheeran       4.0
# 6       1.0       John H.            Reputation     Taylor Swift       3.0
# 7       1.0       John H.        Red Pill Blues         Maroon 5       5.0

Answer 2

使用条件：

import pandas as pd

df_excel = pd.ExcelFile('Sales.xlsx')
df = df_excel.parse('Info')

for col in list(df):  # All columns
    pprow = 0
    prow = 1
    for row in df[1:].iterrows():  # All rows, except first
        if pd.isnull(df.loc[prow, 'Album Name']):  # If this cell is empty all in the same row too.
            continue
        elif pd.isnull(df.loc[prow, col]) and pd.isnull(df.loc[row[0], col]):  # If a cell and next one are empty, take previous valor. 
            df.loc[prow, col] = df.loc[pprow, col]
        pprow = prow
        prow = row[0]

输出（我用不同的名字）：

    Order_ID Customer_name    Album Name
0        NaN           NaN         Radio
1        1.0          John            a 
2        1.0          John             b
3        1.0          John             c
4        1.0          John             d
5        1.0          John             e
6        1.0          John             f
7        NaN           NaN            GE
8        2.0         Harry   We are Born
9        3.0        Lizzy        Relapse
10       4.0           Abe         Smoke
11       4.0           Abe       Tell me
12       NaN           NaN           NaN
13       NaN           NaN      Best Buy
14       5.0        Kristy      The wall
15       6.0         Sammy  Kind of blue