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python - 如何将 Pandas DataFrame 行的迭代结果存储在新列中？

问题描述

我是 Python 编码的新手。目前，我正在尝试分析包含多个工作流的数据框。每个工作流程都有用于启动和结束工作流程的不同流程步骤。在简化版本中，我的数据如下所示：

   Workflow Initiate   End_1   End_2   End_3
0         1   Name_1      na  Name_1      na
1         2   Name_2      na      na      na
2         3   Name_3      na      na  Name_5
3         4   Name_4  Name_5      na      na
4         5       na      na      na  Name_5

对于每个工作流，我想比较结束工作流的名称是否与启动工作流的名称不同。

以下列方式遍历行给了我想要的输出：

for index, row in df.iterrows():
    if ((row['Initiate'] != 'na')
        and (row['Initiate'] == row['End_1']) |
            (row['Initiate'] == row['End_2']) |
            (row['Initiate'] == row['End_3'])
        ):
        print("Name end equals initiate")
    elif ((row['End_1'] == 'na') &
          (row['End_2'] == 'na') &
          (row['End_3'] == 'na')
         ):
        print("No name ended")
    else:
        print("Different name ended")

Name end equals initiate
No name ended
Different name ended
Different name ended
Different name ended

但是，我想在显示每个工作流背后的上述结果的数据框中添加一个额外的列，例如“分析”。

为此，我将代码填充到一个函数中：

def function_name(a, b, c, d):
    for index, row in df.iterrows():
        if ((a != 'na')
            and (a == b) |
                (a == c) |
                (a == d)
            ):
            return "Name end equals initiate"
        elif ((b == 'na') &
              (c == 'na') &
              (d == 'na')
             ):
            return "No name ended"
        else:
            return "Different name ended"

df['Analysis'] = function_name(row['Initiate'],
                               row['End_1'],
                               row['End_2'],
                               row['End_3'])

print(df)

   Workflow Initiate          ...            End_3              Analysis
0         1   Name_1          ...               na  Different name ended
1         2   Name_2          ...               na  Different name ended
2         3   Name_3          ...           Name_5  Different name ended
3         4   Name_4          ...               na  Different name ended
4         5       na          ...           Name_5  Different name ended

如您所见，输出与第一次分析不同。我想在我的数据框中添加一个额外的列，它可以提供与打印语句相同的输出。

标签： pythonpandasloopsdataframe

解决方案

您应该在这里避免按行循环。您的算法是可矢量化的：

df = df.replace('na', np.nan)  # replace string 'na' with NaN for efficient processing
ends = df.filter(like='End')  # filter by columns with 'End'

match = ends.ffill(1).iloc[:, -1] == df['Initiate']  # find last Name in each End
nulls = ends.isnull().all(1)  # check which rows are all null

# apply vectorised conditional logic
df['Result'] = np.select([match, nulls], ['Name end equals initiate', 'No name ended'],
                         'Different name ended')

print(df)

   Workflow Initiate   End_1   End_2   End_3                    Result
0         1   Name_1     NaN  Name_1     NaN  Name end equals initiate
1         2   Name_2     NaN     NaN     NaN             No name ended
2         3   Name_3     NaN     NaN  Name_5      Different name ended
3         4   Name_4  Name_5     NaN     NaN      Different name ended
4         5      NaN     NaN     NaN  Name_5      Different name ended

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