How can I get a column that contains the maximum value of a specific header in panda dataframe?

Suppose I have a table like this:

I want to get a column that has the greatest price from meat type chicken,like this:

what should I do?

You can use idxmax() function. First, filter to select rows where the type is chicken, then find the index of max 'Price':

df.loc[df[df['Meat type'] == 'chicken']['Price'].idxmax()]

Use a filter to select only the rows where the meat type is "chicken", and then use the "max" function to find the row with the highest price.

import pandas as pd    

df = pd.DataFrame({
    'Meat type': ['beef', 'beef', 'chicken', 'chicken', 'pork', 'pork'],
    'brand': ['A', 'B', 'A', 'B', 'A', 'B'],
    'Price': [10, 12, 11, 14, 9, 16]
})   

chicken_df = df[df['Meat type'] == 'chicken']    

max_row = chicken_df.loc[chicken_df['Price'].idxmax()]

print(max_row)

Out:

Meat type    chicken
brand              B
Price             14
Name: 3, dtype: object

Filter only chicken first. Then sort by price and take top 1.

df[df['Meat type'] == 'chicken'].sort_values(by='price', ascending=False).head(1)

df[df['Meat'].eq('chicken')].sort_values('Price').iloc[-1]

Explanation

eq is like ==

I am looking for the rows where Meat is Chicken, then sort Price values.

Default is ascending order.

So I get the last one with using of iloc[-1]