How to make a "side view of the explosion ()" in pandas

Question

I want to do this:

# input: AB 0 [1, 2] 10 1 [5, 6] -20 # output: AB 0 1 10 1 2 10 2 5 -20 3 6 -20 

Each column A value is a list

 df = pd.DataFrame({'A':[[1,2],[5,6]],'B':[10,-20]}) df = pd.DataFrame([[item]+list(df.loc[line,'B':]) for line in df.index for item in df.loc[line,'A']], columns=df.columns) 

The above code may work, but it is very slow

Is there any smart method?

thanks

Answer 1

Method 1 (OP)

 pd.DataFrame([[item]+list(df.loc[line,'B':]) for line in df.index for item in df.loc[line,'A']], columns=df.columns) 

Method 2 (feast)

 df1 = df.A.apply(pd.Series).stack().rename('A') df2 = df1.to_frame().reset_index(1, drop=True) df2.join(df.B).reset_index(drop=True) 

Method 3 (feast)

 A = np.asarray(df.A.values.tolist()) B = np.stack([df.B for _ in xrange(A.shape[1])]).T P = np.stack([A, B]) pd.Panel(P, items=['A', 'B']).to_frame().reset_index(drop=True) 

Thanks @ user113531 for the link to Alexander's answer. I had to change it to work.

Method 4 (@Alexander) RELATED ANSWER

(Follow the link and above if this was helpful)

 rows = [] for i, row in df.iterrows(): for a in row.A: rows.append([a, row.B]) pd.DataFrame(rows, columns=df.columns) 

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Delays

Method 4 (Alexander) is best followed by Method 3