如何删除 python 中具有非数字数据的行

Question

Amount column consists of texts

I have a column which is supposed to be an integer which is saved as object in the DataFrame. I tried to remove the columns which are not numeric by using the below codes:

df[df.columns[8]] = df[df.columns[8]].apply(pd.to_numeric, errors='coerce').fillna(0).astype(float).astype(int).dropna()

But the code is not working. I tried to replace the texts with 0 but its not working.

Answer 1

This will render string rows to NAs.

df["Amount in USD"] = pd.to_numeric(df["Amount in USD"], errors='coerce')

Then just filter out rows which has NAs.

df = df[df["Amount in USD"].notnull()]