如何将 Pandas 中的一列扩展为多列？
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How to expand one column in Pandas to many columns?
提问by Liu Chong
As the title, I have one column (series) in pandas, and each row of it is a list like [0,1,2,3,4,5]. Each list has 6 numbers. I want to change this column into 6 columns, for example, the [0,1,2,3,4,5]will become 6 columns, with 0is the first column, 1is the second, 2is the third and so on. How can I make it?
作为标题，我在 Pandas 中有一个列（系列），它的每一行都是一个像[0,1,2,3,4,5]. 每个列表有 6 个数字。我想把这一列改成6列，比如[0,1,2,3,4,5]将变成6列，有0第一列，1第二列，2第三列等等。我怎样才能做到？
回答by piRSquared
Not as fast as @jezrael's solution. But elegant :-)
不如@jezrael 的解决方案快。但优雅:-)
applywith pd.Series
apply和 pd.Series
df.a.apply(pd.Series)
0 1 2 3 4 5
0 0 1 2 3 4 5
1 0 1 2 3 4 5
or
或者
df.a.apply(pd.Series, index=list('abcdef'))
a b c d e f
0 0 1 2 3 4 5
1 0 1 2 3 4 5
回答by jezrael
You can convert lists to numpy arrayby valuesand then use DataFrameconstructor:
您可以将列表转换为numpy arraybyvalues然后使用DataFrame构造函数：
df = pd.DataFrame({'a':[[0,1,2,3,4,5],[0,1,2,3,4,5]]})
print (df)
a
0 [0, 1, 2, 3, 4, 5]
1 [0, 1, 2, 3, 4, 5]
df1 = pd.DataFrame(df['a'].values.tolist())
print (df1)
0 1 2 3 4 5
0 0 1 2 3 4 5
1 0 1 2 3 4 5
cols = list('abcdef')
df1 = pd.DataFrame(df['a'].values.tolist(), columns=cols)
print (df1)
a b c d e f
0 0 1 2 3 4 5
1 0 1 2 3 4 5
回答by Heavy Breathing
If I understood your question correctly, you are looking for a transpose operation.
如果我正确理解了您的问题，那么您正在寻找转置操作。
df = pd.DataFrame([1,2,3,4,5],columns='a')
# .T stands for transpose
print(df.T)
