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Working on real time vehicle sales data. Data collected from https://data.telangana.gov.in/ for performing data cleaning, data analysis, visualization and building reports using Excel/Power BI.

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Tungana-Bhavya/VEHICLE_SALES_DATA_ANALYSIS_AND_VISUALIZATION

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VEHICLE_SALES_DATA_ANALYSIS_AND_VISUALIZATION

Contents

  1. Title
  2. Tools Used
  3. Description of Dataset
  4. Importing Data & Combining Multiple CSV files
  5. Filtering and Removing Duplicates & Unnecessary Columns
  6. Data Transformation
  7. Error Handling and Data Merging
  8. Loading Cleaned Data into Excel/PowerBI for further analysis

Tools Used

Microsoft Power Query Editor through MS-Excel/PowerBI

Description of Dataset

The vehicle sales data has been collected from the Regional Transport Authority Vehicle Online Sales Data through a website https://data.telangana.gov.in/. The data between January 2023 to January 2024 were collected for performing data analysis and visualization using Business Intelligence Tool. The Excel files from January 2023 to January 2024 were combined using Microsoft Power Query Editor. The vehicle sales data consists of record_number, sl_no, modelDesc, fuel, color, vehicleClass, makeYear, seatCapacity, insuranceValidity, secondVehicle, tempRegistration, category, makerName, officecd, fromDate and toDate.

Importing Data & Combining Multiple CSV files

The various csv files containing sales data for vehicles were kept together in a folder, from January 2023 to August 2023. The vehicle sales folder was loaded using power query editor.

From Power Query tab, choose From File option, select From Folder options then type the folder path or browse the relevant folder from the dialog box.
Power Query -> From File -> From Folder -> Type or paste folder path or browse folder location -> Click Ok

From Diaglog box, the required option as Combine & Edit were selected as shown below.

After selecting Combine & Edit option, the dialog box appears as below:

After pressing ok button, by default, the power query editor will automatically check and applies the correct data type for all the columns. This step is automatically recorded in the Applied Steps. Sometimes, the given data type for the columns may not be correct. Then, data type can be changed by selecting the specific column and choosing the required data type from the Transform tab option.

Power Query -> From Transform -> Data Type: Any list -> Select required data type

Removing Unnecessary Columns

The vehicle sales data consists of 16 columns such as record_number, sl_no, modelDesc, fuel, color, vehicleClass, makeYear, seatCapacity, insuranceValidity, secondVehicle, tempRegistrationNumber, category, makerName, officecd, fromDate and toDate. From the vehicle sales data, 8 unwanted columns as record_number, sl_no, makeYear, seatCapacity, insuranceValidity, secondVehicle, officecd and toDate were removed by selecting all the columns and choosing Remove Columns from home menu or right clicking mouse on the one of the selected column and choose Remove option as shown in the image below.

Power Query Editor -> Home -> Remove Columns List -> Remove Columns

Removing Duplicates

The duplicates from the vehicle sales data were removed based on the tempRegistrationNumber, after selecting the column and choosing Remove Duplicates from Remove Rows list.

Power Query Editor -> Home -> Remove Rows list -> Remove Duplicates

Filtering Columns

The power query filters were applied to the vehicle sales data, illustrated below, based on the non-transport category.

As shown below, the rows of vehicle sales data were filtered according to the type of vehicle, such as motorcars.

Data Transformation

- Inserting new column
The new column year were inserted based on fromdate by using Column From Examples from Add Column tab.

Select column -> Add Column -> Column From Examples -> From Selection ->Select the checkbox for the required column(fromdate selected)

- Data Type Changing or Applying
The data type for the particular column can be applied or changed by selecting the specific column and choosing the required data type from the Transform tab option or simply by selecting the icon on the left side of the column heading.

Power Query -> From Transform -> Data Type: Any list -> Select required data type

- Removing and Reordering Columns
The column named fromDate from vehicle sales data were removed and also data columns were reordered as year, tempRegistrationNumber, category, fuel, vehicleClass, modelDescription, makerName and color.

About

Working on real time vehicle sales data. Data collected from https://data.telangana.gov.in/ for performing data cleaning, data analysis, visualization and building reports using Excel/Power BI.

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