AI DATA ANALYSIS

This code is a Jupyter notebook that contains a series of code cells for an individual analysis done for a concrete data group.

The expected output and information discuss for each individual cell should be:

1. The first code cell imports the necessary libraries for data manipulation and visualization.

2. The second code cell reads a CSV file from a URL and stores it in a pandas DataFrame.

3. The third code cell performs some data cleaning and transformation on the DataFrame, including converting a column of datetime objects to a separate column for each component (hour, month, date, day of the week).

4. The fourth code cell filters the DataFrame to only include rows where the "events" column is not null. The fifth code cell calculates the minimum and maximum datetime values in the DataFrame.

5. The sixth code cell creates a new datetime index that spans the same time range as the original data, but with a frequency of one hour.

6. The seventh code cell calculates the difference between the expected datetime index and the actual datetime index, which gives us a list of missing datetime values.

7. The eighth code cell counts the number of occurrences of each datetime value in the DataFrame.

8. The ninth code cell filters the DataFrame to only include rows where the datetime value appears more than once.

9. The tenth code cell displays the first few rows of the DataFrame.

Install

To run this project, you will need to install the following tools

pandas seaborn matplotlib

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