使用函数重命名多个熊猫数据框列名

Question

Trying to rename pandas dataframe column using regex, I know how to do it rename the list as per below but could not get success results with df.rename.

Input:

df.columns.values = ['Time', '101 <RoomTemperature> (C)', '102 <ChemberTemperature> (C)', '103 <U1100> (C)', '103 <U1200 (C)', '103 U1500> (C)']

Trials of the Renaming dataframe column as per below code using regex but it does not work. I could not think of how to put multiple instruction together in df.rename method.

df.rename(columns={c: c.strip() for c in df.columns.values.tolist()
                                if "<" and ">" in c: 
                  re.search(r"(?<=<).*(?=>)",c).group(0)}, inplace=True)

I want it to follow regex and rename it to as per below:

df.columns.values = ["Time", "RoomTemperature", "ChemberTemperature", "U1100", "103 <U1200 (C)", "103 U1500> (C)"]

Answer 1

You could extract the functionality into a function and do the following:

import re
import pandas as pd

# sample data 
df = pd.DataFrame(
    columns=['Time', '101 <RoomTemperature> (C)', '102 <ChemberTemperature> (C)', '103 <U1100> (C)', '103 <U1200 (C)',
             '103 U1500> (C)'])


# replacement function 
def repl(name):
    match = re.search(r"<(.*?)>", name)
    return match.group(1) if match else name


df.rename(columns={c: repl(c.strip()) for c in df.columns}, inplace=True)

print(df.columns)

Output

Index(['Time', 'RoomTemperature', 'ChemberTemperature', 'U1100',
       '103 <U1200 (C)', '103 U1500> (C)'],
      dtype='object')

That being said, you also need to fix your regular expression.

Answer 2

You can use regular expressions to extract the matching group as per your requirements and then you can use DataFrame.rename to alter the column labels.

Try this:

import re

col_dict = {}
for col in df.columns:
    mobj = re.search(r"\<(.*?)\>", col)
    if mobj:
        col_dict[col] = mobj.group(1)

df.rename(columns=col_dict, inplace=True)

After renaming df.columns will be:

['Time', 'RoomTemperature', 'ChemberTemperature', 'U1100', '103 <U1200 (C)', '103 U1500> (C)']

Answer 3

Another solution, regex can have some unfriendly look about it, despite its power:

columns = ['Time', '101 <RoomTemperature> (C)', '102 <ChemberTemperature> (C)', '103 <U1100> (C)', '103 <U1200 (C)', '103 U1500> (C)']
df = pd.DataFrame([[1,2,3,4,5,6]],columns=columns)

   p = re.compile(r'((?<=<).*?(?=>))')

  #create a dict for the replacement

  replace_dict = {w:p.search(w).group() for w in df.columns if p.search(w)}

 #pass dictionary into rename method

 df.rename(columns=replace_dict)