如何调整Pandas GroupBy输出的DataFrame并导出为指定格式CSV

Here's how you can transform your grouped data into the exact CSV format you need:

Step 1: Reset the Multi-Index #

Your final_df has a multi-index (ID, Seq, float) from the initial groupby operation. First, convert these index levels into regular columns to simplify subsequent aggregation:

final_df = final_df.reset_index()

Step 2: Aggregate Data by ID #

Group the cleaned data by ID, then combine the Seq and float columns into comma-separated strings (we deduplicate Seq values to match your target output):

import pandas as pd

# Aggregate columns into the desired format
aggregated_df = final_df.groupby('ID').agg(
    # Deduplicate Seq entries and join with commas
    Sequence=('Seq', lambda x: ','.join(x.unique())),
    # Convert float values to strings and join with commas
    float=('float', lambda x: ','.join(map(str, x)))
).reset_index()

Step 3: Export to CSV #

Export the aggregated data to a CSV file with no headers, no index, and non-numeric values wrapped in double quotes:

import csv

aggregated_df.to_csv(
    'output.csv',
    index=False,
    header=False,
    quoting=csv.QUOTE_NONNUMERIC  # Ensures string columns are enclosed in "
)

Final Output Preview #

The resulting output.csv will match your requested format exactly:

3631,"D,P,R","1.31,1.45,1.44"
3633,"D,P","1.26,1.27,1.32,1.33"

内容的提问来源于stack exchange，提问作者nimals1986