Last updated 2/2023
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz
Language: English | Size: 2.14 GB | Duration: 4h 16m
Start learning data analysis with these beginners friendly projects
What you’ll learn
Data Analytics Projects solved with Python
Basic Data Science
Python Libraries – Pandas, Matplotlib, Numpy
Python Programming Language
All projects are Solved, and available with Python Source Codes files & dataset files
These projects can be used in Resume/CV, college submission
Requirements
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
Description
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] 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 AnalysisSome 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.You can enroll in our another course also : “Python For Data Science”
Overview
Section 1: Python Data Analytics Projects
Lecture 1 Project 1 – Weather Data Analysis
Lecture 2 Project 2 – Cars Data Analysis
Lecture 3 Project 3 – Police Data Analysis
Lecture 4 Project 4 – Covid-19 Data Analysis
Lecture 5 Project 5 – London Housing Data Analysis
Lecture 6 Project 6 – Census Data Analysis
Lecture 7 Project 7 – Udemy Data Analysis
Lecture 8 Project 8 – Netflix Data Analysis
Beginners looking for job as a Data Analyst,Students searching for projects to submit in college/institute,Anyone interested in Data Science and Data Analytics
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