FREE Python – Data Analytics – Real World Hands-on Projects

Data Science Lovers (YouTube)

Last Updated on March 1, 2023 by GeeksGod

In this course, we have uploaded 8 Data Analytics Projects, solved with Python.

These projects can used if you are looking for a starting level job as a Data Analyst.

If you are a student, you can use these projects to submit in college/institute.

The source codes and datasets files are available to download.

All the projects are created with a very easy explanation.

We have mainly used the popular Python Pandas Library, along with Matplotlib to solve these projects.

Kindly subscribe ‘Data Science Lovers’ on YouTube and show your support.

To buy our Data Analyst Study Material , you can mail us at [email protected]

The projects are :

Project 1 – Weather Data AnalysisProject 2 – Cars Data AnalysisProject 3 – Police Data AnalysisProject 4 – Covid Data AnalysisProject 5 – London Housing Data AnalysisProject 6 – Census Data AnalysisProject 7 – Udemy Data AnalysisProject 8 – Netflix Data Analysis

Some basic examples of commands used in these projects are :

* head() – It shows the first N rows in the data (by default, N=5).

* shape – It shows the total no. of rows and no. of columns of the dataframe

* index – This attribute provides the index of the dataframe

* columns – It shows the name of each column

* dtypes – It shows the data-type of each column

* unique() – In a column, it shows all the unique values. It can be applied on a single column only, not on the whole dataframe.

* nunique() – It shows the total no. of unique values in each column. It can be applied on a single column as well as on the whole dataframe.

* count – It shows the total no. of non-null values in each column. It can be applied on a single column as well as on the whole dataframe.

* value_counts – In a column, it shows all the unique values with their count. It can be applied on a single column only.

* info() – Provides basic information about the dataframe.* size – To show No. of total values(elements) in the dataset.

* duplicated( ) – To check row wise and detect the Duplicate rows.

* isnull( ) – To show where Null value is present.

* dropna( ) – It drops the rows that contains all missing values.

* isin( ) – To show all records including particular elements.

* str.contains( ) – To get all records that contains a given string.

* str.split( ) – It splits a column’s string into different columns.

* to_datetime( ) – Converts the data-type of Date-Time Column into datetime[ns] datatype.

* dt.year.value_counts( ) – It counts the occurrence of all individual years in Time column.

* groupby( ) – Groupby is used to split the data into groups based on some criteria.

* sns.countplot(df[‘Col_name’]) – To show the count of all unique values of any column in the form of bar graph.

* max( ), min( ) – It shows the maximum/minimum value of the series.

* mean( ) – It shows the mean value of the series.

Udemy Coupon :


What you will learn :

1. Data Analytics Projects solved with Python
2. Basic Data Science
3. Python Libraries – Pandas, Matplotlib, Numpy
4. Python Programming Language
5. All projects are Solved, and available with Python Source Codes files & dataset files
6. These projects can be used in Resume/CV, college submission

100% off Coupon