如何在循环期间向数据帧添加新的原始数据并满足特定条件？

Question

我想在迭代到达具有 'total charges' 的原始数据时添加一个新行。仅供参考：如代码所示，第 1 列是必须执行的位置。

python
for row in df.itertuples():
    row[1] == 'Total Charges'

this is how the data look like, i need to separate it with a row, right under total charges

Answer 1

使用：

import pandas as pd
s = list(range(3))
s.append('Total Charges')
s.extend(list(range(3)))
df = pd.DataFrame({'c1': s, 'c2': range(7)})
ind = df[df['c1']=='Total Charges'].index
df.loc[ind[0]+.5]='',''
df = df.sort_index().reset_index()
del df['index']

输出：

Answer 2

希望我理解正确（我使用了您提供的数据示例）。迭代行并搜索 Total Charges。然后使用 pandas.concat().

import pandas as pd

df = pd.DataFrame({'column1': ['data_row_1', 'data_row_2', 'Total Charges', 'data_row_3', 'data_row_4'], 'column2': range(1, 6)})

for index, row in df.iterrows():
    if row['column1'] == 'Total Charges':
        df_before = df.iloc[:index+1]
        df_after = df.iloc[index+1:]
        new_row = pd.DataFrame({'column1': ['new_data_1'], 'column2': ['new_data_2']})
        new_df = pd.concat([df_before, new_row, df_after], ignore_index=True)
        break

print(new_df)

输出：

         column1     column2
0     data_row_1           1
1     data_row_2           2
2  Total Charges           3
3     new_data_1  new_data_2
4     data_row_3           4
5     data_row_4           5

如何在循环期间向数据帧添加新的原始数据并满足特定条件？

how to add new raw to the data frame during a loop and a certain condition is met?

python

data-analysis

pandas

data-science