如何将列表连接到 Pandas 中的数据框
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How to concatenate lists to dataframe in Pandas
提问by Erhan Rden
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?
我想要做的是连接列表（不同长度）并制作数据框。我无法使用 zip()s 实现它。有什么简单的方法吗？
采纳答案by jpp
You can feed concatwith 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.
您可以concat使用系列列表而不是数据框列表进行馈送。对于可变数量的变量，字典是一个好主意，它允许您将未来的列名存储为键。
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
