[SOLVED] How to convert rows into columns (as value but not header) in Python


In the following dataset, I need to convert each row for the “description” under “name" column (for example, inventory1, inventory2 and inventory3) into two separate columns (namely description1 and description2, respectively). If I used either pviot_table or groupby, the value of the description will become header instead of a value under a column. What would be the way to generate the desired output? Thanks

import pandas as pd
df1 = { 'item':['item1','item2','item3','item4','item5','item6'],
  'description':['sales number decrease compared to last month', 'Sales number 
decreased','sales number increased','Sales number increased, need to keep kpi','no sales this 
month','item out of stock']}


desired output as below:
enter image description here


You can actually use pd.concat:

new_df = pd.concat([
            .drop('description', axis=1)
            pd.DataFrame([pd.Series(l) for l in df.groupby('name')['description'].agg(list).tolist()])


>>> new_df
    item        name  code                                  description0                              description1
0  item1  inventory1     1  sales number decrease compared to last month                    Sales number decreased
1  item3  inventory2     2                        sales number increased  Sales number increased, need to keep kpi
2  item5  inventory3     3                           no sales this month                         item out of stock

One-liner version of the above, in case you want it:

pd.concat([df.drop_duplicates('name').drop('description', axis=1).reset_index(drop=True), pd.DataFrame([pd.Series(l) for l in df.groupby('name')['description'].agg(list).tolist()]).add_prefix('description')], axis=1)

Answered By – richardec

Answer Checked By – Gilberto Lyons (BugsFixing Admin)

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