Python 如何从 Pandas DataFrame 获取值而不是索引和对象类型
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How to get a value from a Pandas DataFrame and not the index and object type
提问by Eduardo
Say I have the following DataFrame
假设我有以下 DataFrame
Letter Number A 1 B 2 C 3 D 4
Which can be obtained through the following code
可以通过以下代码获得
import pandas as pd
letters=pd.Series(('A', 'B', 'C', 'D'))
numbers=pd.Series((1, 2, 3, 4))
keys=('Letters', 'Numbers')
df=pd.concat((letters, numbers), axis=1, keys=keys)
Now I want to get the value C from the column Letters.
现在我想从字母列中获取值 C。
The command line
命令行
df[df.Letters=='C'].Letters
will return
将返回
2 C Name: Letters, dtype: object
How can I get only the value C and not the whole two line output?
我怎样才能只得到值 C 而不是整个两行输出？
采纳答案by valkn0t
df[df.Letters=='C'].Letters.item()
This returns the first element in the Index/Series returned from that selection. In this case, the value is always the first element.
这将返回从该选择返回的索引/系列中的第一个元素。在这种情况下，该值始终是第一个元素。
EDIT:
编辑：
Or you can run a loc() and access the first element that way. This was shorter and is the way I have implemented it in the past.
或者您可以运行 loc() 并以这种方式访问第一个元素。这是更短的，是我过去实施它的方式。
回答by EdChum
Use the valuesattribute to return the values as a np array and then use [0]to get the first value:
使用该values属性将值作为 np 数组返回，然后用于[0]获取第一个值：
In [4]:
df.loc[df.Letters=='C','Letters'].values[0]
Out[4]:
'C'
EDIT
编辑
I personally prefer to access the columns using subscript operators:
我个人更喜欢使用下标运算符访问列：
df.loc[df['Letters'] == 'C', 'Letters'].values[0]
This avoids issues where the column names can have spaces or dashes -which mean that accessing using ..
这避免了列名可以有空格或破折号的问题-，这意味着使用..
回答by Lewis
import pandas as pd
dataset = pd.read_csv("data.csv")
values = list(x for x in dataset["column name"])
>>> values[0]
'item_0'
edit:
编辑：
actually, you can just index the dataset like any old array.
实际上，您可以像任何旧数组一样索引数据集。
import pandas as pd
dataset = pd.read_csv("data.csv")
first_value = dataset["column name"][0]
>>> print(first_value)
'item_0'
