Convert data frame columns to rows

Question

I have a dataframe which looks like:

time             feature_1   feature_2 feature_3
02.07.2019 00:00  0.1          0.1        0.7
02.07.2019 00:15  0.2          0.4        0.6
02.07.2019 00:30  0.3          0.5        0.7

I want to convert it to

time              feature    value
02.07.2019 00:00  feature_1   0.1      
02.07.2019 00:00  feature_2   0.1   
02.07.2019 00:00  feature_3   0.7

....

I tried df.melt command but not given any results

`I tried df.melt command but not given any results` and how did you try? `df.melt(id_vars='time')` should do — yatu, Sep 23 '19 at 09:50
dataFrame.melt(id_vars =["time"], var_name ="feature", value_name= 'value') — sr227, Sep 23 '19 at 09:56

Bharat Gera · Accepted Answer · 2019-09-23T10:07:37.753

3

Find the code below:

import pandas
pd.melt(df,id_vars=['time'],value_vars=['feature_1','feature_2','feature_3']).sort_values('time')

edited Sep 23 '19 at 10:07

answered Sep 23 '19 at 09:56

Bharat Gera

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This works, but he time order is completly messed up, is there a way to retain the order – sr227 Sep 23 '19 at 10:02
Use .sort_values('time') this would help in retaining the order. – Bharat Gera Sep 23 '19 at 10:05
1

add that also in your answer – Vikas Periyadath Sep 23 '19 at 10:06

Convert data frame columns to rows

1 Answers1