python pandas modify column

Question

I have what has to be considered a syntax question. Doing some data scrubbing where there are numeric fields, that need to be tidied up.

Like this:

20,956
1,006,486
0
0
85,186
77,573

Sometimes there are commas, sometime multiple commas and sometime none.

So my simple mind says, find and replace will fix this.

This works:

def fixComma(strIn):

    return  strIn.replace(","  , ""   )  


dfAssetMeter_a['lastReadingflt']      =  dfAssetMeter_a['LASTREADING'].apply(fixComma).astype(float)

Questions: Is this “Python” way to do this?

Would somebody be kind enough to provide the correct syntax for removing the commas in line.

I thought something like this would work.

     =  dfAssetMeter_a['LASTREADING']. .replace(","  , ""   ) .astype(float)

Answer 1

You can use the str accessor along with replace, and pandas.to_numeric:

import pandas as pd

df = pd.DataFrame(
    {
        "LASTREADING": [
            "20,956",
            "1,006,486",
            "0",
            "0",
            "85,186",
            "77,573",
        ]
    }
)

df["lastReadingflt"] = pd.to_numeric(df["LASTREADING"].str.replace(",", ""))

  LASTREADING  lastReadingflt
0      20,956           20956
1   1,006,486         1006486
2           0               0
3           0               0
4      85,186           85186
5      77,573           77573