df.query while using pandas in python produces empty results

Question

I am learning how to manipulate data using pandas in python. I got the following script:

import pandas as pd

df = pd.read_table( "t.txt" )    #read in the file
df.columns = [x.strip() for x in df.columns]   #strip spaces in headers
df = df.query('TLD == ".biz"')     #select the rows where TLD == ".biz"
df.to_csv('t.txt', sep='\t')  #write the output to a tab-separated file

but the output file has no records, headers only. When I check using

print.df

prior to the selection, the output is:

             TLD  Length                                              Words  \
0       .biz           5                                                ...   
1       .biz           4                                                ...   
2       .biz           5                                                ...   
3       .biz           5                                                ...   
4       .biz           3                                                ...   
5       .biz           3                                                ...   
6       .biz           6                                                ...

So I know the column TLD has rows with the .biz values. I also tried :

>>> print(df.loc[df['TLD'] == '.biz'])

but the results is

Empty DataFrame

With list of my columns

What am I doing wrong please?

jezrael · Accepted Answer · 2017-03-16 06:35:33Z

5

It seems some whitespaces are there, so need remove them by strip:

print(df.loc[df['TLD'].str.strip() == '.biz'])

df['TLD'] = df['TLD'].str.strip()
df = df.query('TLD == ".biz"')

edited Mar 16, 2017 at 6:35

answered Mar 16, 2017 at 6:29

jezrael

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3 Comments

TomEus Over a year ago

Thanks! Just out of curiosity - how did you recognized white spaces beign there? To my untrained eye it all look good

jezrael Over a year ago

because you remove whitespaces in columns, so I think in data are too ;)

jezrael Over a year ago

and maybe simplier for remove whitespaces in columns is df.columns = df.columns.str.strip()

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