Question

我有一个像这样的Pandas DataFrame（摘自官方教程）：

d = {'one' : pd.Series([1., 2., 3.], index=['a', 'b', 'c']),
     'two' : pd.Series([1., 2., 3., 4.], index=['a', 'b', 'c', 'd'])}

DF = pd.DataFrame(d)

我想添加一个列表（或元组）作为DataFrame属性

DF.Attribute = ['Some random','infos in','a list']

它过去工作正常，但由于我最近更新了Pandas（版本0.21.0），我收到此警告：

UserWarning: Pandas doesn't allow columns to be created via a new attribute name - see https://pandas.pydata.org/pandas-docs/stable/indexing.html#attribute-access
  DF.Attribute = ['Some random','infos in','a list']

你知道如何避免这种警告吗？

Answer 1

使用[]，但因为df长度越少Series需要按length过滤L = ['Some random','infos in','a list'] DF['Attribute'] = pd.Series(L, index=DF.index[:len(L)]) print (DF) one two Attribute a 1.0 1.0 Some random b 2.0 2.0 infos in c 3.0 3.0 a list d NaN 4.0 NaN：

d = {'one' : pd.Series([1., 2., 3.], index=['a', 'b', 'c']),
     'two' : pd.Series([1., 2., 3., 4.], index=['a', 'b', 'c', 'd'])}

DF = pd.DataFrame(d)
DF.columns.name = "The title of my DataFrame"
print (DF)
The title of my DataFrame  one  two
a                          1.0  1.0
b                          2.0  2.0
c                          3.0  3.0
d                          NaN  4.0

print (DF.columns.name)
The title of my DataFrame

编辑：

DF.columns.name = None
print (DF)
   one  two
a  1.0  1.0
b  2.0  2.0
c  3.0  3.0
d  NaN  4.0

删除它：

DF = DF.rename_axis("The title of my DataFrame", axis=1)
print (DF)

The title of my DataFrame  one  two
a                          1.0  1.0
b                          2.0  2.0
c                          3.0  3.0
d                          NaN  4.0

替代set_index：

A = 10, 
A(minus) = 9, 
B = 8, 
B(minus) = 7, 
C = 6, 
C(minus) = 5

Pandas：将列表存储为DataFrame属性

1 个答案: