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Task 1 : Data Visualisation The data.csv contains more than eighty thousand earthquake events in Indonesia. The features or columns in the original file of
Task : Data Visualisation The data.csv contains more than eighty thousand earthquake events in Indonesia. The features or columns in the original file of data.csv are date, time, latitude, longitude, depth, and magnitude. Save the data.csv into a data frame variable of dfRawXXXX. Before doing the data analysis and data visualisation to give insight into the dataset, add date, month, year, earthquake category and depth category features to the dataset by using the following code: a Date, month and year features b Earthquake category c Depth category Visualise the data using as many data visualisation techniques as possible in Python by importing the seaborn module and the matplotlib.pyplot module to get the insight.
Task : Data Visualisation
The data.csv contains more than eighty thousand earthquake events in Indonesia. The features
or columns in the original file of data.csv are date, time, latitude, longitude, depth, and
magnitude. Save the data.csv into a data frame variable of dfRawXXXX. Before doing the data
analysis and data visualisation to give insight into the dataset, add date, month, year, earthquake
category and depth category features to the dataset by using the following code:
a Date, month and year features
b Earthquake category
c Depth category
Visualise the data using as many data visualisation techniques as possible in Python by
importing the seaborn module and the matplotlib.pyplot module to get the insight.
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