将 Pandas 系列作为一行添加到 Pandas DataFrame

Question

我正在尝试将 aPandas.Series作为新行添加到 a 中Pandas.DataFrame。然而，系列似乎总是被添加，其索引显示为单独的行。

我们如何将其附加为单行？

import pandas as pd

df = pd.DataFrame([
    ('Tom', 'male', 10),
    ('Jane', 'female', 7),
    ('Peter', 'male', 9),
], columns=['name', 'gender', 'age'])
df.set_index(['name'], inplace=True)
print(df)

       gender  age
name              
Tom      male   10
Jane   female    7
Peter    male    9

s = pd.Series(('Jon', 'male', 12), index=['name', 'gender', 'age'])
print(s)

name       Jon
gender    male
age         12
dtype: object

预期结果

       gender  age
name              
Tom      male   10
Jane   female    7
Peter    male    9
Jon      male   12

尝试1

df2 = df.append(pd.DataFrame(s))
print(df2)

           0   age  gender
Tom      NaN  10.0    male
Jane     NaN   7.0  female
Peter    NaN   9.0    male
name     Jon   NaN     NaN
gender  male   NaN     NaN
age       12   NaN     NaN

尝试#2

df2 = pd.concat([df, s], axis=0)
print(df2)

           0   age  gender
Tom      NaN  10.0    male
Jane     NaN   7.0  female
Peter    NaN   9.0    male
name     Jon   NaN     NaN
gender  male   NaN     NaN
age       12   NaN     NaN

尝试#3

df2 = pd.concat([df, pd.DataFrame(s)], axis=0)
print(df2)

           0   age  gender
Tom      NaN  10.0    male
Jane     NaN   7.0  female
Peter    NaN   9.0    male
name     Jon   NaN     NaN
gender  male   NaN     NaN
age       12   NaN     NaN

Answer 1

这“有效”，但您可能需要重新考虑如何构建数据框。如果追加数据，请一次性完成所有操作，而不是逐行执行。

>>> pd.concat([df, s.to_frame().T.set_index('name')])
       gender age
name             
Tom      male  10
Jane   female   7
Peter    male   9
Jon      male  12

作为数据框的一列，系列通常都是相同的数据类型（例如age）。在这种情况下，您的系列代表给定记录的单行数据，例如数据库中可能具有混合类型的行。您可能想将您的系列视为数据框行。

row = pd.DataFrame({'gender': 'male', 'age': 12}, 
                   index=pd.Index(['Jon'], name='name'))
>>> pd.concat([df, row])
       gender  age
name              
Tom      male   10
Jane   female    7
Peter    male    9
Jon      male   12
>>> pd.concat([df, row])