如何将pandas DataFrame的第一列作为一个系列？

I tried:

我试过了：

x=pandas.DataFrame(...)
s = x.take([0], axis=1)

And s gets a DataFrame, not a Series.

并获得了一个DataFrame，而不是一个系列。

5 个解决方案

#1

>>> import pandas as pd
>>> df = pd.DataFrame({'x' : [1, 2, 3, 4], 'y' : [4, 5, 6, 7]})
>>> df
   x  y
0  1  4
1  2  5
2  3  6
3  4  7
>>> s = df.ix[:,0]
>>> type(s)
<class 'pandas.core.series.Series'>
>>>

#2

You can get the first column as a Series by following code:

您可以通过以下代码将第一列作为系列获取：

x[x.columns[0]]

#3

in 0.11

In [7]: df.iloc[:,0]
Out[7]: 
0    1
1    2
2    3
3    4
Name: x, dtype: int64

#4

Isn't this the simplest way?

这不是最简单的方法吗？

By column name:

按列名称：

In [20]: df = pd.DataFrame({'x' : [1, 2, 3, 4], 'y' : [4, 5, 6, 7]})
In [21]: df
Out[21]:
    x   y
0   1   4
1   2   5
2   3   6
3   4   7

In [23]: df.x
Out[23]:
0    1
1    2
2    3
3    4
Name: x, dtype: int64

In [24]: type(df.x)
Out[24]:
pandas.core.series.Series

#5

This works great when you want to load a series from a csv file

当您想从csv文件加载系列时，这非常有用

x = pd.read_csv('x.csv', index_col=False, names=['x'],header=None).iloc[:,0]
print(type(x))
print(x.head(10))


<class 'pandas.core.series.Series'>
0    110.96
1    119.40
2    135.89
3    152.32
4    192.91
5    177.20
6    181.16
7    177.30
8    200.13
9    235.41
Name: x, dtype: float64

#1

>>> import pandas as pd
>>> df = pd.DataFrame({'x' : [1, 2, 3, 4], 'y' : [4, 5, 6, 7]})
>>> df
   x  y
0  1  4
1  2  5
2  3  6
3  4  7
>>> s = df.ix[:,0]
>>> type(s)
<class 'pandas.core.series.Series'>
>>>

#2