Number of Observations
There are several aggregate functions in pandas
. One of them is .count()
method, which counts number of non-null observation for each column.
1234567# Importing library import pandas as pd # Reading csv file df = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/67798cef-5e7c-4fbc-af7d-ae96b4443c0a/audi.csv') # Count number of non-null rows print(df.count())
This method is popular for counting number of rows under specific condition. For example, you may count number of cars manufactured after 2015. This time you don't need to see the number of observation in each column, so you can choose particular one.
1234567# Importing library import pandas as pd # Reading csv file df = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/67798cef-5e7c-4fbc-af7d-ae96b4443c0a/audi.csv') # Count number of cars manufactured after 2015 print(df.loc[df.year > 2015, 'model'].count())
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Number of Observations
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There are several aggregate functions in pandas
. One of them is .count()
method, which counts number of non-null observation for each column.
1234567# Importing library import pandas as pd # Reading csv file df = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/67798cef-5e7c-4fbc-af7d-ae96b4443c0a/audi.csv') # Count number of non-null rows print(df.count())
This method is popular for counting number of rows under specific condition. For example, you may count number of cars manufactured after 2015. This time you don't need to see the number of observation in each column, so you can choose particular one.
1234567# Importing library import pandas as pd # Reading csv file df = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/67798cef-5e7c-4fbc-af7d-ae96b4443c0a/audi.csv') # Count number of cars manufactured after 2015 print(df.loc[df.year > 2015, 'model'].count())
Дякуємо за ваш відгук!