在 Pandas 中分组并打印整个数据帧

Question

I have a dataset as below, in this case, I want to count the number of fruits in each country and output as a column in the dataset.

I tried to use groupby, df=df.groupby('Country')['Fruits'].count(),

but in this case I am not getting the expected results as the groupby just outputs the count and not the entire dataframe/dataset.

It would be helpful if someone can suggest a better way to do this.

Dataset

Country     Fruits      Price       Sold            Weather     

India       Mango       200         Market          sunny
India       Apple       250         Shops           sunny
India       Banana      50          Market          winter
India       Grapes      150         Road            sunny
Germany     Apple       350         Supermarket     Autumn
Germany     Mango       500         Supermarket     Rainy
Germany     Kiwi        200         Online          Spring
Japan       Kaki        300         Online          sunny
Japan       melon       200         Supermarket     sunny

Expected Output

Country     Fruits      Price       Sold            Weather     Number

India       Mango       200         Market          sunny       4
India       Apple       250         Shops           sunny       4
India       Banana      50          Market          winter      4
India       Grapes      150         Road            sunny       4
Germany     Apple       350         Supermarket     Autumn      3
Germany     Mango       500         Supermarket     Rainy       3
Germany     Kiwi        200         Online          Spring      3
Japan       Kaki        300         Online          sunny       2
Japan       melon       200         Supermarket     sunny       2

Thank you:)

Answer 1

You are looking for transform :

df['count'] = df.groupby('Country')['Fruits'].transform('size')

---

   Country  Fruits  Price         Sold Weather  count
0    India   Mango    200       Market   sunny      4
1    India   Apple    250        Shops   sunny      4
2    India  Banana     50       Market  winter      4
3    India  Grapes    150         Road   sunny      4
4  Germany   Apple    350  Supermarket  Autumn      3
5  Germany   Mango    500  Supermarket   Rainy      3
6  Germany    Kiwi    200       Online  Spring      3
7    Japan    Kaki    300       Online   sunny      2
8    Japan   melon    200  Supermarket   sunny      2