Pd.to_numeric Converts Entire Series To Nan
I'm trying to convert a column using pd.to_numeric, but for some reason it turns all values (except one) into NaN: In[]: pd.to_numeric(portfolio['Principal Remaining'],errors='coer
Solution 1:
read_csv
with thousands=','
df = pd.read_csv('file.csv', thousands=',')
This fixes the problem while reading your data.
replace
and to_numeric
df['Principal Remaining'] = pd.to_numeric(
df['Principal Remaining'].str.replace(',', ''), errors='coerce')
If the first option isn't a choice, you'll need to get rid of the commas first using str.replace
, then call pd.to_numeric
as shown here.
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