How to merge similar rows and split column into rows by values? - pandas

Question

I have this data set for example:
Name Number Is true
0 Dani 2 yes
1 Dani 2 no
2 Jack 5 no
3 Jack 5 maybe
4 Dani 2 maybe
I want to create a new data set that combines similar rows and adds columns by column different values. This is the output I'm trying to get:
Name Number Is true1 Is true2 Is true3
0 Dani 2 yes no maybe
1 Jack 5 no maybe
I couldn't get it working from example 10 here:
How to pivot a dataframe
Would you be able to provide a specific example for this use case please?
Thanks.
Edit for respond:
Name yes no maybe
0 Dani 2 2 2
1 Jack NaN 5 5

Answer 1

With combination of pivot_table(...) and apply(...):
df.pivot_table(index=["Name", "Number"], values="Is true", aggfunc=list).apply(lambda x: pd.Series({f"Is true{id+1}": el for id, el in enumerate(x[0])}), axis=1).reset_index()
Output:
Name Number Is true1 Is true2 Is true3
0 Dani 2 yes no maybe
1 Jack 5 no maybe NaN
Edit
For your follow up. This might be something along the lines, what you're looking for:
df.pivot_table(index=["Name"], columns="Is true", values="Number", aggfunc=list).fillna('').apply(lambda x: pd.Series({f"{col}{id+1}": el for col in x.keys() for id, el in enumerate(x[col])}), axis=1).reset_index()
Output:
Name maybe1 no1 yes1
0 Dani 2.0 2.0 2.0
1 Jack 5.0 5.0 NaN

Answer 2

You can try this:
df2 = df.drop_duplicates(subset=['Name', 'Number Is'])
df2 = df2.reset_index(drop=True).assign(true= df.groupby('Number Is')['true'].agg(list).reset_index(drop=True) )
temp = df2['true'].apply(pd.Series).T
temp.index = temp.index+1
temp = temp.T
df2 = df2.assign(**temp.add_prefix('true').add_suffix(' Is')).drop(columns='true').fillna('')
output:
Name Number Is true1 Is true2 Is true3 Is
0 Dani 2 yes no maybe
1 Jack 5 no maybe