DataFrame列值处理：提取首个元素，正则替换失效求助

Your current regex isn’t working because it’s targeting digits after the comma (\d+), but your values have letters (like D,A,C). Let’s fix this with two straightforward, reliable approaches:

Approach 1: Split on Comma and Take the First Element #

This is the most intuitive method for this task. Split each string at the comma, then grab the first item from the resulting list:

df["col name"] = df["col name"].astype(str).str.split(',').str[0]

• str.split(',') turns each string into a list (e.g., 'D,A,C' becomes ['D', 'A', 'C'])
• str[0] extracts the first element of each list (so ['D', 'A', 'C'] simplifies to 'D')

Approach 2: Fixed Regex Replace #

If you prefer using regex, adjust your pattern to match any character after the comma instead of just digits. Use r',.*' which means "comma followed by zero or more of any character":

df["col name"] = df["col name"].astype(str).str.replace(r',.*', '', regex=True)

• ,.* matches a comma and everything that comes after it
• Replacing that match with an empty string leaves only the first element before the comma

Both methods will transform your original array from:
array(['A','B','C','D','D,A,C','B,A'], dtype=object)
to your desired result:
array(['A','B','C','D','D','B'], dtype=object)

Pick the approach that feels most readable to you—they’ll both get the job done perfectly!

内容的提问来源于stack exchange，提问作者tbone