Free Udemy Course: 8 Python Projects - Data Analysis

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 code 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 to solve these projects.Kindly go through the description of each video lecture for more details.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 AnalysisSome examples of commands used in these projects are :The commands that we used in this project :* 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.