Delete row in column when value in column is a string

Question

I have the following dataframe:

           MATERIAL KW_WERT NETTO_EURO                 TA  
0           S    0.15       18.9                   D  
1            S   0.145      18.27                  D  
2            S   0.145      18.27                  D  
7            S   3.011     252.92                 AN  
8            S   3.412     429.91                 AN  
9            S     0.9      113.4                 AN  
14           S   0.007         KW             N  
15          S     0.3      46.05          SONSTIGES

how can I filter for the datatype (string) in the column NETTO_EURO an delete it?

The point is that the basic data I get includes some errors and I cant sum up the columns with a string data in it. Now is the first solution to delete the row. Later I will try to fix it otherwise.

Damian · Accepted Answer · 2020-11-26 12:20:38Z

1

You can use mask with to_numeric and notnull with boolean indexing:

print (pd.to_numeric(df.NETTO_EURO, errors='coerce').notnull())
0      True
1      True
2      True
3      True
4      True
5      True
6      True
7      True
8      True
9      True
10     True
11     True
12     True
13    False
14    False
15     True
Name: NETTO_EURO, dtype: bool

print (df[pd.to_numeric(df.NETTO_EURO, errors='coerce').notnull()])
   MATERIAL  KW_WERT NETTO_EURO          TA
0    S    0.150       18.9         H
1    S    0.145      18.27         H
2    S    0.145      18.27         H
3    S    0.150       18.9         H
4    S    0.150       18.9         H
5    S    0.145      18.27         H
6    S    0.150       18.9         H
7    S    3.011     252.92  AN
8    S    3.412     429.91  AN
9    S    0.900      113.4  AN
10   S    0.281       23.6  AN
11   S    0.078       9.83  AN
12   S    0.107      13.48  AN
15  S    0.300      46.05   SONSTIGES

If has old version of pandas use convert_objects:

print (df[df["NETTO_EURO"].convert_objects(convert_numeric=True).notnull()])
   MATERIAL  KW_WERT NETTO_EURO          TA
0    S    0.150       18.9         H
1    S    0.145      18.27         H
2    S    0.145      18.27         H
3    S    0.150       18.9         H
4    S    0.150       18.9         H
5    S    0.145      18.27         H
6    S    0.150       18.9         H
7    S    3.011     252.92  AN
8    S    3.412     429.91  AN
9    S    0.900      113.4  AN
10   S    0.281       23.6  AN
11   S    0.078       9.83  AN
12   S    0.107      13.48  AN
15  S    0.300      46.05   SONSTIGES

edited Nov 26, 2020 at 12:20

Damian

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answered Aug 3, 2016 at 11:06

jezrael

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5 Comments

Damian Over a year ago

thanks for your answer.. but i get and "invalid string" at this point errors='coerce' because of the =

jezrael Over a year ago

There is problem with old version of pandas. What is your version? print (pd.show_versions())

Damian Over a year ago

i got pandas 0.16.2

jezrael Over a year ago

I think there is problem. Can you upgrade to last version of pandas, 0.18.1?

Damian Over a year ago

unfortunately not... im working on a company computer! Therefore i cant install anything.. i have to use what is given...

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