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.
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The projects are :
Project 1 - Weather Data Analysis
Project 2 - Cars Data Analysis
Project 3 - Police Data Analysis
Project 4 - Covid Data Analysis
Project 5 - London Housing Data Analysis
Project 6 - Census Data Analysis
Project 7 - Udemy Data Analysis
Project 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.
* Learn Data Analysis with Python
* Learn Basic Data Science
* Learn about Python Libraries - Pandas, Matplotlib, Numpy
* Learn Python Programming Language
* Use these projects in Resume/CV, college submission
* All projects are Solved, and available with Python Source Codes files & dataset files
* Beginners Friendly Projects - Required only basic Python language knowledge
* You can use Jupyter notebook, Google Colab etc to run the python code
* All datasets & source codes are available to download with this course
* This course is for beginners as well as intermediate level ... You will enjoy it