KeyError：熊猫数据框中的错误

Question

import pandas as pd

businesses = pd.read_json(businesses_filepath, lines=True, encoding='utf_8')
restaurantes = businesses['Restaurants' in businesses['categories']]

I would like to remove the lines that do not have Restaurants in the categories column, and this column has lists, however gave the error 'KeyError: False' and I would like to understand why and how to solve.

Answer 1

The expression 'Restaurants' in businesses['categories'] returns the boolean value False . This is passed to the brackets indexing operator for the DataFrame businesses which does not contain a column called False and thus raises a KeyError.

What you are looking to do is something called boolean indexing which works like this.

businesses[businesses['categories'] == 'Restaurants']

Answer 2

If you find that your data contains spelling variations or alternative restaurant related terms, the following may be of benefit. Essentially you put your restaurant related terms in restuarant_lst . The lambda function returns true if any of the items in restaurant_lst are contained within each row of the business series. The .loc indexer filters out rows which return false for the lambda function.

restaurant_lst = ['Restaurant','restaurantes','diner','bistro']
restaurant = businesses.loc[businesses.apply(lambda x: any(restaurant_str in x for restaurant_str in restaurant_lst))]

Answer 3

The reason for this is that the Series class implements a custom in operator that doesn't return an iterable like the == does, here's a workaround

businesses[['Restaurants' in c for c in list(businesses['categories'])]]

hopefully this helps someone where you're looking for a substring in the column and not a full match.

Answer 4

I think what you meant was :

businesses = businesses.loc[businesses['categories'] == 'Restaurants']

that will only keep rows with the category restaurants

Answer 5

None of the answers here actually worked for me,

businesses[businesses['categories'] == 'Restaurants']

obviously won't work since the value in 'categories' is not a string, it's a list, meaning the comparison will always fail.

What does , however, work, is converting the column into tuples instead of strings:

businesses['categories'] = businesses['categories'].apply(tuple)

That allows you to use the standard .loc thing:

businesses.loc[businesses['categories'] == ('Restaurants',)]