在不知道索引的情况下获取系列的第一个元素[重复]

[英]Get first element of Series without knowing the index [duplicate]

本文翻译自 Hello lad 查看原文 2014/06/17 45919 pandas/ head/ python/ series/ dataframe

This question already has an answer here:

这个问题在这里已有答案:

Pandas - Get first row value of a given column 5 answers

Pandas - 获取给定列5个答案的第一行值

Is that any way that I can get first element of Seires without have information on index.

这是否可以获得Seires的第一个元素而没有索引信息。

For example,We have a Series

例如,我们有一个系列

    import pandas as pd
    key='MCS096'
    SUBJECTS=pd.DataFrame({'ID':Series([146],index=[145]),\
                   'study':Series(['MCS'],index=[145]),\
                   'center':Series(['Mag'],index=[145]),\
                   'initials':Series(['MCS096'],index=[145])
                   })

prints out SUBJECTS:

打印出SUBJECTS:

    print (SUBJECTS[SUBJECTS.initials==key]['ID'])
    145    146
    Name: ID, dtype: int64

How can I get the value here 146 without using index 145?

如何在不使用索引145的情况下获取此值146?

Thank you very much

非常感谢你

1 个解决方案

#1

Use iloc to access by position (rather than label):

使用iloc按位置访问(而不是标签):

In [11]: df = pd.DataFrame([[1, 2], [3, 4]], ['a', 'b'], ['A', 'B'])

In [12]: df
Out[12]: 
   A  B
a  1  2
b  3  4

In [13]: df.iloc[0]  # first row in a DataFrame
Out[13]: 
A    1
B    2
Name: a, dtype: int64

In [14]: df['A'].iloc[0]  # first item in a Series (Column)
Out[14]: 1

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