替换字符串中的第一个值 dataframe pandas

Question

I need to replace the specific values in every row of pandas df with another value. My data looks like this:

time        log
1         whats the weather look like today
2         what is the weather look like today
3         whats for lunch
4         what’s for lunch

I need to replace whats to be what is and what’s to be what is also. The desired output:

time        log
1         what is the weather look like today
2         what is the weather look like today
3         what is for lunch
4         what is for lunch

I have tried:

new_df = df.log.str.replace("^whats", "what is").str.replace("^what’s", "what is")

This took care of whats but not the other case and the outcome is not a pandas df and I need it to be pandas df.

Answer 1

What you are getting is a Pandas Series, if you want to get a DataFrame, just use

new_df = pd.DataFrame(df.log.str.replace("^whats", "what is").str.replace("^what’s", "what is"))

And as was pointed out by @Quang Hoang, you can search using the pandas OR and search either for whats or what’s :

new_df = pd.DataFrame(df.log.str.replace("^whats|what’s", "what is"))

Full code:

import pandas as pd

df = pd.DataFrame({"time": [1,2,3,4],
    "log": ['whats the weather look like today', 'what is the weather look like today', 'whats for lunch', 'what’s for lunch']
             })
new_df = pd.DataFrame(df.log.str.replace("^whats", "what is").str.replace("^what’s", "what is"))

and the results are:

print(df)
   time                                  log
0     1    whats the weather look like today
1     2  what is the weather look like today
2     3                      whats for lunch
3     4                   what’s for lunch

print(new_df)
                                   log
0  what is the weather look like today
1  what is the weather look like today
2                    what is for lunch
3                    what is for lunch