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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.
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This comprehensive free online course on Udemy covers everything you need to become proficient in Python-based data analysis. Whether you're a beginner or looking to advance your skills, this free Udemy course with certificate provides hands-on training and practical knowledge you can apply immediately.
This free certification course is perfect for anyone looking to break into data science or enhance their existing skills. Here's who will benefit most from this no-cost training opportunity:
Learn from Data Science Lovers, an experienced professional team in data analytics education. With a proven track record of creating accessible, project-based courses, they've helped thousands of students master complex data concepts through practical application. Their teaching style focuses on clear explanations and real-world examples that build confidence and competence.
With an impressive 4.42 rating and 14,550 students already enrolled, this Udemy free course has proven its value. The course includes 3 comprehensive lessons and X hours of video tutorials, all taught in English. What sets this free online course apart is the hands-on project approach using real datasets from weather, automotive, healthcare, housing, and entertainment industries. Upon completion, you'll receive a certificate to showcase on LinkedIn and your resume. Plus, with mobile access, you can learn anytime, anywhereβperfect for busy professionals. This Development course in the Data Science niche is regularly updated and includes lifetime access, meaning you can revisit materials whenever you need a refresher.
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Here's why this free certification course is an opportunity you can't afford to miss: Data analysts earn median salaries over $70,000 and demand is growing 25% annually. These 8 portfolio projects give you real-world experience with Python Pandas, the #1 data analysis library. Unlike theoretical courses, you'll build actual projects employers want to see. Plus, with lifetime access, you're investing in skills that pay dividends for years. This zero-cost entry into data science could be the career-changing opportunity you've been waiting for.
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