带条件的If语句操作及从DataFrame的column$date提取年份（102009→2009）

1. Conditional If Statement to Extract 4 Characters #

Let's start with the first task—assuming you're working with a value (numeric or string) where you need to validate a condition before pulling 4 characters. Since your second task involves grabbing a year from 102009, I'll use extracting the last 4 digits as an example (adjust the slicing if you need characters from a different position):

input_val = 102009  # Could also be a string like "102009"

# Convert to string to handle both numeric and string inputs
input_str = str(input_val)

# Conditional check: ensure the input has at least 4 characters
if len(input_str) >= 4:
    extracted_chars = input_str[-4:]
    print(f"Extracted 4 characters: {extracted_chars}")
else:
    print("Input is too short to extract 4 characters!")

This snippet first standardizes the input to a string, checks if it meets the length requirement, then slices the last 4 characters. Swap [-4:] with [:4] if you need the first 4 characters instead.

2. Extract Year from DataFrame's column$date Column #

Moving on to your pandas DataFrame problem—since column$date has values like 102009 (6-digit numbers/strings), we can use pandas' built-in string tools to pull the year (last 4 digits) efficiently:

import pandas as pd

# Sample DataFrame matching your scenario
df = pd.DataFrame({"column$date": [102009, 052015, 122022]})

# Convert column to string, extract last 4 digits, and cast back to integer (optional)
df["extracted_year"] = df["column$date"].astype(str).str[-4:].astype(int)

print(df)

Sample Output: #

column$date  extracted_year
0        102009            2009
1         52015            2015
2        122022            2022

If your column$date values are already stored as strings, you can skip the astype(str) step. This method processes the entire column in one go, which is perfect for pandas workflows.

内容的提问来源于stack exchange，提问作者BEN