如何基于Python DataFrame首行年份格式化月份（Python 2.7）

Hey there! Since you're a beginner working with Python 2.7 and pandas, let's break this down into simple, actionable steps to get your desired output.

Step-by-Step Breakdown #

First, let's clarify our goals:

• Pull the start and end years from the first row's 2017-18 value (we'll get 2017 and 2018)
• Locate where DEC sits in the month row
• Append the start year to all months up to and including DEC, and the end year to every month after that

Full Working Code (Python 2.7 Compatible) #

import pandas as pd

# Your original DataFrame
df = pd.DataFrame([['2017-18','','','','','','','','','','',''], 
                   ['APR', 'MAY', 'JUN', 'JULY', 'AUG', 'SEP', 'OCT', 'NOV', 'DEC', 'JAN', 'FEB', 'MAR']])

# Step 1: Extract start and end years from the first row
year_range = df.iloc[0, 0]  # Grab the '2017-18' value
start_year = year_range.split('-')[0]  # Get '2017'
# Convert '18' to '2018' by prepending '20'
end_year = '20' + year_range.split('-')[1]

# Step 2: Find the index position of 'DEC' in the month row
month_row = df.iloc[1]
dec_index = month_row[month_row == 'DEC'].index[0]

# Step 3: Format each month with the correct year
formatted_months = []
for idx, month in enumerate(month_row):
    if idx <= dec_index:
        # Use .format() instead of f-strings (f-strings don't work in Python 2.7)
        formatted_month = "{}-{}".format(month, start_year)
    else:
        formatted_month = "{}-{}".format(month, end_year)
    formatted_months.append(formatted_month)

# Step 4: Create the new DataFrame with formatted months
df1 = df.copy()
df1.iloc[1] = formatted_months

# Check the result
print(df1)

Expected Output #

When you run the code, df1 will match exactly what you requested:

0          1          2          3          4          5          6          7          8          9          10         11
0  2017-18                                                                                                                        
1  APR-2017  MAY-2017  JUN-2017  JULY-2017  AUG-2017  SEP-2017  OCT-2017  NOV-2017  DEC-2017  JAN-2018  FEB-2018  MAR-2018

Quick Tips for Beginners #

• We use iloc to access rows/columns by their numerical position (since your DataFrame doesn't have named labels)
• Python 2.7 doesn't support modern f-strings, so we rely on the .format() method for string concatenation
• This code will automatically adjust to different year ranges (like 2018-19) without manual edits

内容的提问来源于stack exchange，提问作者PratikSharma