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The data is presented in csv format and has the following format: Attribute Description TripId The id of a trajectory TimeStep The record number for
The data is presented in csv format and has the following format:
Attribute
Description
TripId
The id of a trajectory
TimeStep
The record number for a point of a trajectory
TimeStamp
The timestamp for a point of a trajectory
Speed
The ground velocity
Acceleration
The rate of change of speed
Heading
The bearing which is a value between and
Latitude
The latitude coordinate of GPS observation
Longitude
The longitude coordinate of GPS observation
You can download the file here: data.csvDownload data.csv
You should read the CSV file into a Pandas Data frame and use Pandas to perform the tasks listed below.
These tasks are designed to give you an opportunity to demonstrate the following learning outcomes and to satisfy the assessment criteria:
Clean irregularities in the raw data file to convert it into a proper CVS format.
Read data from the cleaned CVS file into a Pandas Data frame.
Convert between different Datetime formats.
Filterrestrict the rows and columns in Pandas Data frames to help answer the queries.
Use aggregation operations such as mean, median, sum, max and to summarize data.
Use group by to summarize data for various categories.
Create new columns that are computed based on other existing columns.
Demonstrate appropriate use of a variety of types of Plots to visualize data using Pandas
All plots should have meaningful titles, axes labels and userfriendly data labels and be scaled large enough to easy see the details required.
Markdown headings should be added to clearly separate and explain each of the tasks and markdown should be provided to discusssummarize the key observations.
Dont repeat yourself use functions to avoid duplicating the same logic in multiple places.
Use programming best practice write clear simple Python code and use wellchosen identified names for all variables and functions.
Note that the raw CSV data may require "cleaning" before it can be processed. Everything should be included in a single Jupyter notebook which you will need to create yourself no skeleton solution for this assignment
Tasks:
Use markdown to document the data cleaning that you performed.
Read the cleaned CSV file into a Pandas data frame
Convert the timestamp into an YYYYMMDDHHMMSS format
Convert speed from mileshour to kilometrehour
Add a column that shows the accumulated time driven for each vehicle
Show the minimum and maximum speed for each trip in a plot
Plot the speed profile for trip T
Add a column that indicates if a vehicle moves straight or is turning leftright
Plot the trajectories of all vehicles. Use a loop to go thorugh all the trajectories.
Add a column that indicates hard braking where deceleration is larger than ms
Plot a bar chart showing the travel time of each vehicle in ascending order
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