[英]Pandas selection not filtering rows based on values in columns?
I was practicing data wrangling and I eneded up with this simple dataset.我正在练习数据整理,并使用了这个简单的数据集。 but then I started to filter and selecting some information on it but is not working
但后来我开始过滤并选择一些信息但不工作
here is the data set:这是数据集:
https://drive.google.com/file/d/1d1FMWhh3U1KnfVFYyC5R5USuB2BbcN6S/view?usp=sharing https://drive.google.com/file/d/1d1FMWhh3U1KnfVFYyC5R5USuB2BbcN6S/view?usp=sharing
df.head()
0 TCS
1 Accenture
2 Cognizant
3 ICICI Bank
4 HDFC Bank
...
8996 Bitla Software
8997 Kern Liebers
8998 ANAAMALAIS TOYOTA
8999 Elsevier
9000 Samsung Heavy Industries
Name: campany_name, Length: 9001, dtype: object
We see here that Accenture is in the second row but when I try to call it is not working我们在这里看到埃森哲在第二排,但是当我尝试调用它时它不起作用
df['campany_name'] == 'Accenture'
0 False
1 False
2 False
3 False
4 False
...
8996 False
8997 False
8998 False
8999 False
9000 False
I don't really want to get a different way.我真的不想换一种方式。 I just want to understand what is happening under the hood and fully understand what is different in this data set that I can't just do it like I normaly do.
我只是想了解幕后发生的事情,并完全了解这个数据集中有什么不同,我不能像往常那样做。 which is df['campany_name] == 'Accenture' I should get boolenans, and with those id be able to get the row doing df[df['campany_name] == 'Accenture']
这是 df['campany_name] == 'Accenture' 我应该得到布尔值,并且有了这些 id 就可以得到执行 df[df['campany_name] == 'Accenture'] 的行
something must be wrong at the index or format level.索引或格式级别一定有问题。 but I mean i'm new to python.
但我的意思是我是 python 的新手。
Do做
df['campany_name'] = df['campany_name'].astype(str)
and then you can try:然后你可以尝试:
df.query('campany_name == Accenture')
or或者
df[df['campany_name'] == 'Accenture']
and if you know the row and column and you are trying to retrieve just one value you can do:如果你知道行和列,并且你试图只检索一个值,你可以这样做:
df.at[1, 'campany_name']
Also, remember that you are just printing information, if you need to save the result, assign it to something eg:另外,请记住,您只是在打印信息,如果您需要保存结果,请将其分配给例如:
acc_row = df.query('campany_name == Accenture')
As you are trying to filter the dataframe given only a string, you can use df.Series.str.contains
当您尝试过滤仅给定字符串的 dataframe 时,您可以使用
df.Series.str.contains
aaa[aaa['campany_name'].str.contains('Accenture')]
campany_name ... jobs interviews
1 Accenture ... 4600.0 2500.0
5814 Accenture Federal Services ... NaN 20.0
[2 rows x 10 columns]
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