CODEWITHSUNDEEP
pythonpython-3.xpandasdataframe
Chethan
Chethan

Reputation: 611

Repeat a particular row in pandas n no. of times in pandas and increase a count for every repeat in a column

I have a dataframe

df_in = pd.DataFrame([["A","X",5,4,1],["B","Y",3,3,1],["C","Y",4,7,4]], columns=['col1', 'col2', 'col3', 'col4','col5'])

I want to repeat a row n no. of times and the count also should increase from the no. present in col4.

Ex: I want to repeat the B row 3 times and count in col4 will increse from the current value present in col4 like 3,4 and 5. Similarly for C row repeat 2 times and increase the count in col4 from the current value.

Expected Output:

df_Out = pd.DataFrame([["A","X",5,4,1],["B","Y",3,3,1],["B","Y",3,4,1],["B","Y",3,5,1],["C","Y",4,7,4],["C","Y",4,8,4]], columns=['col1', 'col2', 'col3', 'col4','col5'])

How to do it?

Upvotes: 1

Views: 315

Answers (1)

jezrael
jezrael

Reputation: 862641

Create dictionary for number of repeating, map by Series.map and if no match set 1, then use Index.repeat for index values with DataFrame.loc for append rows, last add counter by GroupBy.cumcount for col4:

d = {'B':3, 'C':2}

df = df_in.loc[df_in.index.repeat(df_in['col1'].map(d).fillna(1))]
df['col4'] += df.groupby(level=0).cumcount()
df = df.reset_index(drop=True)
print (df)
  col1 col2  col3  col4  col5
0    A    X     5     4     1
1    B    Y     3     3     1
2    B    Y     3     4     1
3    B    Y     3     5     1
4    C    Y     4     7     4
5    C    Y     4     8     4

Upvotes: 2

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