CODEWITHSUNDEEP
pythonpandas
Lostsoul
Lostsoul

Reputation: 25999

How can I create multiple rows from a single row based on a formula?

I'm struggling to create multiple rows from one in Pandas. For example, assuming I have this data:

df = pd.DataFrame({"Name": ["Bob", "Mary", "Amy"], "Age": [22, 35, 58], "EarningsYearly": [100,200,50],})
df['Quarterly'] = df['EarningsYearly']/4
df

        Name Age  EarningsYearly    Quarterly
0       Bob  22   100               25.0
1       Mary 35   200               50.0
2       Amy  58   50                12.5

I can take early and turn it into quarterly but I actually want a new line for each so I can process each separately later. So my expected output is:

enter image description here

How can I do it? Also another similar question is can I generate the new lines within the command I used to create the Quarterely column? Or should I create it first then add new rows?

Upvotes: 2

Views: 714

Answers (2)

SeaBean
SeaBean

Reputation: 23217

You can use .loc + df.index.repeat() + reset_index(), as follows:

df_out = df.loc[df.index.repeat(4)].reset_index(drop=True)

Result

print(df_out)

    Name  Age  EarningsYearly  Quarterly
0    Bob   22             100       25.0
1    Bob   22             100       25.0
2    Bob   22             100       25.0
3    Bob   22             100       25.0
4   Mary   35             200       50.0
5   Mary   35             200       50.0
6   Mary   35             200       50.0
7   Mary   35             200       50.0
8    Amy   58              50       12.5
9    Amy   58              50       12.5
10   Amy   58              50       12.5
11   Amy   58              50       12.5

Upvotes: 0

Scott Boston
Scott Boston

Reputation: 153460

Use:

df.reindex(df.index.repeat(4)).reset_index(drop=True)

Output:

    Name  Age  EarningsYearly  Quarterly
0    Bob   22             100       25.0
1    Bob   22             100       25.0
2    Bob   22             100       25.0
3    Bob   22             100       25.0
4   Mary   35             200       50.0
5   Mary   35             200       50.0
6   Mary   35             200       50.0
7   Mary   35             200       50.0
8    Amy   58              50       12.5
9    Amy   58              50       12.5
10   Amy   58              50       12.5
11   Amy   58              50       12.5

Upvotes: 4

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