CODEWITHSUNDEEP
pandasdataframepython-3.5
RustyShackleford
RustyShackleford

Reputation: 3677

Why is column name not going over actual column and creating new columns in dataframe?

I am assigning column names to a dataframe in pandas but the column names are creating new columns how do I go around this issue?

What dataframe looks like now:

                                     abs_subdv_cd  abs_subdv_desc
0  A0001A    ASHTON                              ...             NaN
1  A0002A    J. AYERS                            ...             NaN
2  A0003A    NEWTON ALLSUP                       ...             NaN
3  A0004A    M. AUSTIN                           ...             NaN
4  A0005A    RICHARD W. ALLEN                    ...             NaN

What I want dataframe look like:

 abs_subdv_cd  abs_subdv_desc
0  A0001A    ASHTON                              
1  A0002A    J. AYERS                            
2  A0003A    NEWTON ALLSUP                       
3  A0004A    M. AUSTIN                           
4  A0005A    RICHARD W. ALLEN

code so far: 

import pandas as pd

###Declaring path###
path = ('file_path')

###Calling file in folder###
appraisal_abstract_subdv = pd.read_table(path + '/2015-07-28_003820_APPRAISAL_ABSTRACT_SUBDV.txt',
                             encoding = 'iso-8859-1' ,error_bad_lines = False,
                             names = ['abs_subdv_cd','abs_subdv_desc'])
print(appraisal_abstract_subdv.head())

-edit-

When I try appraisal_abstract_subdv.shape..the dataframe is showing shape as (4000,1) where as the data has two columns.

this example of data I am using:

A0001A    ASHTON                                  
A0002A    J. AYERS

Thank you in advance.

Upvotes: 1

Views: 49

Answers (2)

MaxU - stand with Ukraine
MaxU - stand with Ukraine

Reputation: 210982

it looks like your data file has another delimiter (not a TAB, which is a default separator for pd.read_table()), so try to use: sep='\s+' or delim_whitespace=True parameter.

In order to check your columns after reading your data file do the following:

print(df.columns.tolist())

Upvotes: 1

James Russo
James Russo

Reputation: 568

There is a rename function in pandas that you can use to get the column names

appraisal_abstract_subdv.columns.values

then with those column names use this method to rename them appropriately

df.rename(columns={'OldColumn1': 'Newcolumn1', 'OldColumn2': 'Newcolumn2'}, inplace=True)

Upvotes: 1

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