[英]Pandas groupby 2 coluns/conditions then value_counts() by another column?
Here's what the dataset I'm working on looks like:这是我正在处理的数据集的样子:
Type![]() |
SubType![]() |
Municipality![]() |
---|---|---|
Social Media![]() |
Facebook ![]() |
New Castle![]() |
Onground![]() |
Campus![]() |
Monroe![]() |
Onground![]() |
Cafe![]() |
Kutlski![]() |
Social Media![]() |
Instagram ![]() |
New Castle![]() |
Social Media![]() |
Tiktok![]() |
San Andreas![]() |
Social Media![]() |
Facebook ![]() |
New Castle![]() |
Social Media![]() |
Facebook ![]() |
San Andreas![]() |
I want to group it by Type and SubType then further filter it by Municipality and then value_counts()
it.我想按Type和SubType对它进行分组,然后按Municipality进一步过滤它,然后
value_counts()
它。
Here's what I've tried:这是我尝试过的:
ab = df.groupby([df['Type'] == 'Social Media',
df['SubType']])
ab['Municipality'].value_counts()
I almost got what I want only that it shows everything, not just the result of the condition (under the Type column, it has 'true' and false' section.我几乎得到了我想要的,只是它显示了所有内容,而不仅仅是条件的结果(在“类型”列下,它有“真”和“假”部分。
This is the result I'm looking for:这是我正在寻找的结果:
Type![]() |
SubType![]() |
Municipality![]() |
|
---|---|---|---|
Social Media![]() |
Facebook ![]() |
New Castle![]() |
2 ![]() |
San Andreas![]() |
1 ![]() |
||
Instagram ![]() |
New castle![]() |
1 ![]() |
|
TikTok![]() |
San Andreas![]() |
1 ![]() |
But instead, this is my result:但相反,这是我的结果:
Type![]() |
SubType![]() |
Municipality![]() |
|
---|---|---|---|
True![]() |
Facebook ![]() |
New Castle![]() |
2 ![]() |
San Andreas![]() |
1 ![]() |
||
Instagram ![]() |
New Castle![]() |
1 ![]() |
|
Titkok![]() |
San Andreas![]() |
1 ![]() |
|
False![]() |
Onground![]() |
Cafe![]() |
1 ![]() |
Campus![]() |
1 ![]() |
||
and so on...![]() |
.... ![]() |
.... ![]() |
... ![]() |
Just filter first and group only by subtype.只需先过滤并仅按子类型分组。
df.query('Type == `Social Media`').groupby('SubType')['Municipality'].value_counts()
I think value_counts is what you are looking for我认为 value_counts 是你要找的
df.value_counts(['Type','SubType','Municipality'])
Out[169]:
Type SubType Municipality
Social Media Facebook New Castle 2
Onground Cafe Kutlski 1
Campus Monroe 1
Social Media Facebook San Andreas 1
Instagram New Castle 1
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