Why Does Pandas Only Show the First Group’s Row Labels After Concatenation?

Hello, I am a Python enthusiast.

1. Introduction

In a recent Python community chat, a member asked about a Pandas grouping problem: after splitting a column header string and grouping the DataFrame by the "Fee Period" column, the concatenated result only shows the row label for the first group, while subsequent groups lose their labels.

list1 = '电子税票号码 征收税务机关 社保经办机构 单位编号 费种 征收品目 征收子目 费款所属期 入（退）库日期 实缴（退）金额'
list2 = list1.split(' ')

path_file = r'C:\Users\Administrator\Desktop\提取数据.xlsx'
df = pd.read_excel(path_file)

grouped = df.groupby('费款所属期')
result = []  # store results

for name, group in grouped:
    group.columns = list2
    result.append(group)
    result.append(pd.DataFrame({'费款所属期': ['', '', ''], '实缴（退）金额': ['', '', '']}))

result_df = pd.concat(result, ignore_index=True)

The issue is that using pd.concat in this way only retains the first group's index label in the final DataFrame.

2. Implementation Process

One responder noted that concatenating groups may not be appropriate for this task and recommended writing each group directly to an Excel file instead of reassigning row labels and concatenating.

3. Summary

The discussion presented a concrete Pandas grouping challenge, showed the problematic code, explained why only the first group's label appears after concatenation, and offered a practical alternative of exporting each group separately to Excel.