[英]Iterate through multiple columns in a Panda dataframe and find count unique values
I am working with a dataset which looks like below:我正在使用如下所示的数据集:
I have imported this dataset to my code using the panda library.我已使用熊猫库将此数据集导入到我的代码中。 My goal is to find unique entries of the programming languages from columns 2, 3, 4. I wish the output to be:
我的目标是从第 2、3、4 列中找到编程语言的唯一条目。我希望 output 是:
Python 4
Perl 3
C++ 3
....
Any leads would be helpful任何线索都会有所帮助
Use DataFrame.filter
with DataFrame.stack
and Series.value_counts
:将
DataFrame.filter
与DataFrame.stack
和Series.value_counts
一起使用:
s = df.filter(like='Language').stack().value_counts()
This is an alternative way这是另一种方法
df['lang1'].value_counts() + df['lang2'].value_counts() + df['lang3'].value_counts()
or要么
cols = ['lang1', 'lang2', 'lang2']
sum([df[col].value_counts() for col in cols])
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