INTRODUCTION
The following analysis is based on weather dataset using different machine algorithims to make predictions of a certain weather phenom and fetch for data in various instances.
Dataset Overview
it will efficiently include the main modules i.e pandas which will be used for dataframes,numpy which is for storage of bulk data and matplotlib for data visiualization.
Load Dataset
Data will be obtained from kaggle and loaded into jupyter notebook environment to the specific folder path and also with the full installation of other dependancies like pyforest.
Functions used in Pandas Data Analysis
1.Shape
data.shape
2.Data types
data.dtypes
3.Unique
data['Weather'].value_counts()
4.Count
data.info
5.Describe
data.describe()
Answering different Data analysis Problems
Q1.)Find the records where the weather was exactly clear.
Q2.)Find the number of times the windspeed was exactly 4km/h.
Q3.)Check if there are any NULL values present in the dataset.
Q4.)Rename the column "Weather" to "Weather_Condition"
Q5.)What is the mean visibility of the dataset.
Q6.)Find the number of records where the wind speed is greater than 24km/h and visibility is equal to 25km
Q7.)What is the mean value of each column for each Weather_Conditions.
Q8.)Find all instances where the weather is clear and the relative humidity is greater than 50 or visibility is above 40.
Q9.)Find the number of weather weather conditions that include snow.
Conclusion
Data analysis helps us visualize data graphycally by giving clarity of comparisons of different datasets and comprehend data easily and efficiently.
Top comments (0)