'DataFrame filter column
I have the following dataframe 'X_df'
which city has the 5th highest total number of Walmart stores (super stores and regular stores combined)?
data_url = 'https://raw.githubusercontent.com/plotly/datasets/master/1962_2006_walmart_store_openings.csv'
x_df = pd.read_csv(data_url, header=0)
x_df['STRSTATE'].where(x_df['type_store'] == 7)
Solution 1:[1]
Edit:
I think something like this is what you want? :
data_url = 'https://raw.githubusercontent.com/plotly/datasets/master/1962_2006_walmart_store_openings.csv'
x_df = pd.read_csv(data_url, header=0)
city_store_count = x_df.groupby(['STRCITY']).size().sort_values(ascending = False).to_frame()
city_store_count.columns = ['Stores_in_City']
city_store_count.iloc[4]
The fifth biggest is actually a shared 3rd place with ten stores, so you could print the top 10 for instance:
city_store_count.head(10)
Sources
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Source: Stack Overflow
| Solution | Source |
|---|---|
| Solution 1 |
