在 pandas 系列中寻找价值-Python3 [英] finding values in pandas series - Python3

问题描述

我遇到了一个令人烦恼的问题(我对python还是很陌生的)

i have this excruciatingly annoying problem (i'm quite new to python)

df=pd.DataFrame[{'col1':['1','2','3','4']}]

col1=df['col1']

为什么col1[1] in col1返回False?

推荐答案

对于检查值，请使用 boolean indexing :

For check values use boolean indexing:

#get value where index is 1
print (col1[1])
2 
#more common with loc
print (col1.loc[1])
2

print (col1 == '2')
0    False
1     True
2    False
3    False
Name: col1, dtype: bool

如果需要获取行:

print (col1[col1 == '2'])
1    2
Name: col1, dtype: object

使用or检查多个值:

print (col1.isin(['2', '4']))
0    False
1     True
2    False
3     True
Name: col1, dtype: bool 

print (col1[col1.isin(['2', '4'])])
1    2
3    4
Name: col1, dtype: object

关于in用于测试成员资格的一些信息

And something about in for testing membership docs:

在Series上使用Python in运算符测试索引中的成员身份，而不是值中的成员身份.

Using the Python in operator on a Series tests for membership in the index, not membership among the values.

如果这种行为令人惊讶，请记住，在Python字典上使用in会测试键，而不是值，而Series则类似于dict.要测试值中的成员资格，请使用方法 isin():

If this behavior is surprising, keep in mind that using in on a Python dictionary tests keys, not values, and Series are dict-like. To test for membership in the values, use the method isin():

对于DataFrames，同样适用于列轴，测试列名称列表中的成员资格.

For DataFrames, likewise, in applies to the column axis, testing for membership in the list of column names.

#1 is in index
print (1 in col1)
True

#5 is not in index
print (5 in col1)
False

#string 2 is not in index
print ('2' in col1)
False

#number 2 is in index
print (2 in col1)
True

您尝试在索引值中找到字符串2:

You try to find string 2 in index values:

print (col1[1])
2

print (type(col1[1]))
<class 'str'>

print (col1[1] in col1)
False

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