How to concatenate lists to dataframe in Pandas

Question

c1=["q","q","q","q","q","q"]
c2=["x","x","x","x","x","x"]
c3=["w","w","w","w","w","w"]
ca=["c","e","a","d"]
cb=["y","z","s","f"]
cc=["y","z","s","f"]
df1=pd.DataFrame(c1, columns=['c1'])
df2=pd.DataFrame(c2, columns=['c2'])
df3=pd.DataFrame(c3, columns=['c3'])
df4=pd.DataFrame(ca, columns=['ca'])
df5=pd.DataFrame(cb, columns=['cb'])
df6=pd.DataFrame(cc, columns=['cc'])
df7=pd.concat([df1,df2,df3,df4,df5,df6],axis=1)
df7

What I want to do is concatenate lists (different lengths) and make dataframe. I couldn't realize it using zip()s. Is there any easy way of that?

jpp · Accepted Answer · 2018-07-28 10:28:53Z

4

You can feed concat with a list of series instead of a list of dataframes. A dictionary is a good idea for a variable number of variables, and allows you to store your future column names as keys.

d = {'c1': c1, 'c2': c2, 'c3': c3, 'ca': ca, 'cb': cb, 'cc': cc}

df = pd.concat([pd.Series(v, name=k) for k, v in d.items()], axis=1)

print(df)

  c1 c2 c3   ca   cb   cc
0  q  x  w    c    y    y
1  q  x  w    e    z    z
2  q  x  w    a    s    s
3  q  x  w    d    f    f
4  q  x  w  NaN  NaN  NaN
5  q  x  w  NaN  NaN  NaN

answered Jul 28, 2018 at 10:28

jpp

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