ValueError: Labels not contained in the axis
I have form data:
IMP_START_TIME IMP_CLR_TIME SERV_OR_IOR_ID
0 2017-02-28 23:59:32.8730 2017-03-01 00:11:28.7550 -1447310116
1 2017-03-01 00:00:09.1820 2017-03-01 00:01:06.9120 1673545041
... ... ... ...
266863 2017-03-01 04:05:28.2200 nan 2108335332
266866 2017-03-01 13:10:01.1600 nan -724153592
I want to delete all rows that have "nan" in the IMP_CLR_TIME column. To do this, I wrote the following code:
df = pd.read_csv(r'C:\Users\SIA_1_3_2017.csv',low_memory=False)
SID_ST_CT_col = df[['IMP_START_TIME','IMP_CLR_TIME','SERV_OR_IOR_ID']]
SID_ST_CT_str = SID_ST_CT_col.astype(str)
SID_ST_CT_str.drop(SID_ST_CT_str.loc[SID_ST_CT_str['IMP_CLR_TIME']=='nan'])
But I am getting the following error:
ValueError: labels ['IMP_START_TIME' 'IMP_CLR_TIME' 'SERV_OR_IOR_ID'] not contained in axis
When I print lines that have "nan" in the IMP_CLR_TIME column using the following command, it works. But I cannot figure out why I am getting this error when I try to delete the same lines.
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You seem to need dropna
:
print (df.columns.tolist())
['IMP_START_TIME', 'IMP_CLR_TIME', 'SERV_OR_IOR_ID']
df = df.dropna(subset=['IMP_CLR_TIME'])
print (df)
IMP_START_TIME IMP_CLR_TIME SERV_OR_IOR_ID
0 2017-02-28 23:59:32.8730 2017-03-01 00:11:28.7550 -1447310116
1 2017-03-01 00:00:09.1820 2017-03-01 00:01:06.9120 1673545041
To remove spaces in column names:
df.columns = df.columns.str.strip()
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