Closed sandeepny441 closed 11 months ago
import pandas as pd
data = { 'worker_id': [1, 2, 3, 4, 5], 'first_name': ['Monika', 'Niharika', 'Vishal', 'Amitah', 'Vivek'], 'last_name': ['Arora', 'Verma', 'Singhal', 'Singh', 'Bhati'], 'salary': [100000, 80000, 300000, 500000, 500000], 'joining_date': ['2014-02-20 00:00:00', '2014-06-11 00:00:00', '2014-02-20 00:00:00', '2014-02-20 00:00:00', '2014-06-11 00:00:00'], 'department': ['HR', 'Admin', 'HR', 'Admin', 'Admin'] }
df = pd.DataFrame(data)
How would you use count to find the total number of rows in the DataFrame?
How can you use count to find the number of non-NA/null entries in the 'salary' column?
How would you apply count to find the number of non-NA/null entries for each column in the DataFrame?
Can you use count along with groupby to find out how many workers are in each department?
How can you use count to find out how many unique 'joining_date' values are present in the DataFrame?
How would you use count to determine the number of workers who have a salary greater than 100,000?
Is it possible to use count to find the number of workers with the last name 'Singh'? How would you do it?
Can you apply count to find the number of rows where both 'first_name' and 'last_name' are non-NA/null?
How would you use count to find the number of workers who joined before a certain date, for example, '2014-05-01'?
import pandas as pd
Create a dictionary containing your data
data = { 'worker_id': [1, 2, 3, 4, 5], 'first_name': ['Monika', 'Niharika', 'Vishal', 'Amitah', 'Vivek'], 'last_name': ['Arora', 'Verma', 'Singhal', 'Singh', 'Bhati'], 'salary': [100000, 80000, 300000, 500000, 500000], 'joining_date': ['2014-02-20 00:00:00', '2014-06-11 00:00:00', '2014-02-20 00:00:00', '2014-02-20 00:00:00', '2014-06-11 00:00:00'], 'department': ['HR', 'Admin', 'HR', 'Admin', 'Admin'] }
Create DataFrame
df = pd.DataFrame(data)
How would you use count to find the total number of rows in the DataFrame?
How can you use count to find the number of non-NA/null entries in the 'salary' column?
How would you apply count to find the number of non-NA/null entries for each column in the DataFrame?
Can you use count along with groupby to find out how many workers are in each department?
How can you use count to find out how many unique 'joining_date' values are present in the DataFrame?
How would you use count to determine the number of workers who have a salary greater than 100,000?
Is it possible to use count to find the number of workers with the last name 'Singh'? How would you do it?
Can you apply count to find the number of rows where both 'first_name' and 'last_name' are non-NA/null?
How would you use count to find the number of workers who joined before a certain date, for example, '2014-05-01'?