Data Preparation Q3 Sumalika

Data Pre-Processing:

Dataset: Meteorological Data
Tools & Techniques:
1. JMP
2. Tableau
3. Excel

1. Check for Missing Values in the given data set:
The Meteorological data set given by the weather department consists of few missing values which can be excluded from the analysis. The two rows that contained missing values were discovered using JMP a screenshot of it is provided.

2. Check for Duplicate Values:
Since there is no unique identifier, no issue if duplicate values.
The date field has 1 value for each, hence no repetitions in date value.

3. Analyse variable distributions:

Date: Refers to date fields for Months April, August and December

Wind Direction: Wind direction ranges from o.1 to 359.1 with a mean of 236 degree.

Wind Speed: Wind speed ranges from 0.1 to 6.8 in terms of m/s units.

4. Data Transformation:

- For Wind Speed Trend Analysis: Join Sensor Data with Meteorological data to obtain the trends in wind speed with respect to chemicals.
Step 1: For each date point available in weather data, identify the average wind speed using Pivot Tables.
Step 2: For each date point available in sensor data, identify the sum of reading for the 4 chemicals using Pivot and map it to its respective dates.
Step 3: The data source (final) for wind storm trend analysis is formed by joining both the transformed tables in Step 1 and Step 2. The table is as follows: