问题

import pandas as pd

# Your reference dataframe
reference_df = pd.DataFrame({
    'Product': ['Shirt', 'Sneakers', 'Pants', 'Tennis ball', 'Football ball', 'Football boots'],
    'Brand': ['Zara', 'Nike', 'Zara', 'Wilson', 'Adidas', 'Adidas']
})

# Your dataframe to be filled
df = pd.DataFrame({
    'Product': ['Shirt', 'Shirt', 'Pants', 'Tennis ball', 'Shirt', 'Football boots', 'Football boots', 'Football boots', 'Pants', 'Sneakers', 'Football ball', 'Football boots'],
    'Brand': [None, None, None, None, None, None, None, None, None, None, None, None]
})

# Use map to fill the 'Brand' column based on the 'Product' from the reference dataframe
df['Brand'] = df['Product'].map(reference_df.set_index('Product')['Brand'])

# Print the resulting dataframe
df

This code will fill the 'Brand' column in your dataframe based on the 'Product' using the reference dataframe, giving you the desired output.

df['Brand'] = df['Brand'].map(referencedf.set_index('Product')['Brand'])
df

答案1

得分: 0

df['Brand'] = df['Product'].map(reference_df.set_index('Product')['Brand'])
print(df)

输出：

           Product   Brand
0            衬衫      Zara
1            衬衫      Zara
2            裤子      Zara
3      网球      Wilson
4            衬衫      Zara
5   足球鞋      Adidas
6   足球鞋      Adidas
7   足球鞋      Adidas
8            裤子      Zara
9         运动鞋    Nike
10   足球      Adidas
11  足球鞋      Adidas

df['Brand'] = df['Product'].map(reference_df.set_index('Product')['Brand'])
print(df)

           Product   Brand
0            Shirt    Zara
1            Shirt    Zara
2            Pants    Zara
3      Tennis ball  Wilson
4            Shirt    Zara
5   Football boots  Adidas
6   Football boots  Adidas
7   Football boots  Adidas
8            Pants    Zara
9         Sneakers    Nike
10   Football ball  Adidas
11  Football boots  Adidas