Python Essentials (Online course)

About Course

This beginner-friendly course offers a comprehensive introduction to Python, one of the world’s most popular programming languages. Through hands-on projects and real-world examples, students will learn core Python concepts, including data types, control structures, functions, and object-oriented programming. The course also covers essential libraries for data manipulation and visualization, giving students the foundational skills they need to pursue roles in data science, web development, automation, and more. Whether you’re new to coding or looking to sharpen your skills, Python Essentials provides a solid foundation in one of today’s most versatile languages.

By the end of this course, participants will have the confidence to write Python code, solve problems, and continue their learning journey with advanced topics and specialized fields.

Course Content

Python Essentials
By covering these foundational topics, the course equips learners with the skills to confidently write Python code and build simple programs, preparing them for more advanced programming and data-related courses.

Python Joins- Inner Join in Pandas

03:18
Python Inner Join: How to Join more than 2 Dataframes in Pandas

04:54
Python Joins (Pandas) : How to Merge on multiple columns

01:33
Python Joins: Left Join in Pandas

02:19
Python Joins: Right Join in Pandas

01:22
Python Joins: How to merge/join multiple dataframes with different key column name.

02:19
Python Joins: How to perform a full outer join/outer joins in Pandas.

01:53
Python Joins (Pandas): How to perform self-join in a dataframe

01:58
Python Joins (Pandas): Merging on Index

01:49
Python Joins (Pandas): Join on multi-index (same name)

01:51
Python Joins (Pandas): To Join on Multi-Index (Different index name)

01:54
Python Joins (Pandas): Concatenation

05:09
Python Joins (Pandas): Validating Merge

03:30
Python(Pandas) – Scatter Plot

02:33
Python (Pandas):- Group By and agg( )

04:58
Python (Pandas) – Query ( ) method using ‘AND’ and ‘OR’

03:50
Python (Pandas)- To divide values in one Series/column by values in another Series/column

02:13
Python (Pandas) – Drop columns/series

01:28
Python (Pandas) – Pivoting

01:32
How to find the datatype of a column(s)/Series in Pandas (Python).

00:51
How to change datatype of a column/series in pandas (Python)

01:07
How to rename the column/series in pandas (Python)

01:12
How to find number of rows and column in pandas (Python)

00:24
how to plot multiple valuesets on Y-axis of plot – Matplotlib (python)

01:23
Python (pandas) :- .loc for slicing (part1)

04:11
Python (Pandas) :- .loc for slicing (part2)

01:26
Python (Pandas):- .loc for slicing (part 3)

00:15
Python (Pandas):- .loc for slicing (part-4)

01:43
Python(pandas):- set index/ reset index

02:30
Python (Pandas):- DatetimeIndex

03:02
Python (Pandas):- To parse a column as date while importing csv

01:59
Python (Pandas): Data Exploration and Data Transformation – Part 1

02:58
Python(Pandas): Data Exploration and Data Transformation – Part 2

03:16
Python(Pandas): Data Exploration and Data Transformation (Part 3)

02:55
Python (Pandas): Data Exploration and Data Transformation (Part 4)

03:24
Python (Pandas): Logical AND and Logical OR

01:32
Python (Pandas): isin( ) and not isin ( )

03:44
Python (Pandas): String functions in pandas

04:10
Python (Pandas): Replace method

01:01
Python (Pandas): How to handle Missing values (isna() , dropna(), fillna())

09:08
Python (Pandas) : Value Count

01:40
Python (Pandas) : How to remove Duplicate values (Keep=’first’, ‘last’, False)

01:57
Python (Pandas): Summary Statistics of numerical columns (describe(), std(), quantile(), mode() etc)

06:04
Python (Pandas): isin( ) and not isin( )

02:50
Python (Matplotlib):- Plot linegraph (part1)

03:16
Python(Matplotlib):- Adding xlabel, ylabel, title, figsize (part2)

01:29
Python(Matplotlib):- Marker size, Color, Linestyle, Linewidth etc (part3)

01:21
Python(matplotlib):- various colors, linestyles, markers in plot method (part4)

00:45
Python (Matplotlib):- xlabel, ylabel, title (part 5)

01:02
Python (Matplotlib):- To plot subplots which share same Y-axis

03:22
Twinx() – How to plot a graph with Dual Y axis and same X axis in Python (Matplotlib)

03:01
Python (Matplotlib):- Histogram

04:11
Python (matplotlib):- Bargraphs

03:13
Python (Matplotlib) :- Boxplot

02:49
Python (Matplotlib) :- Scatter Plot

07:49
Python (Matplotlib):- Customizations and style sheets in matplotlib visuals

04:43
Python (Matplotlib):- Saving Matplotlib plots or figures

05:23

Student Ratings & Reviews

5.0

Total 1 Rating

1 Rating

0 Rating

manpreet sidhu

1 month ago

Excellent Course !

About Course

Course Content

Python Essentials By covering these foundational topics, the course equips learners with the skills to confidently write Python code and build simple programs, preparing them for more advanced programming and data-related courses.

Python Joins- Inner Join in Pandas

Python Inner Join: How to Join more than 2 Dataframes in Pandas

Python Joins (Pandas) : How to Merge on multiple columns

Python Joins: Left Join in Pandas

Python Joins: Right Join in Pandas

Python Joins: How to merge/join multiple dataframes with different key column name.

Python Joins: How to perform a full outer join/outer joins in Pandas.

Python Joins (Pandas): How to perform self-join in a dataframe

Python Joins (Pandas): Merging on Index

Python Joins (Pandas): Join on multi-index (same name)

Python Joins (Pandas): To Join on Multi-Index (Different index name)

Python Joins (Pandas): Concatenation

Python Joins (Pandas): Validating Merge

Python(Pandas) – Scatter Plot

Python (Pandas):- Group By and agg( )

Python (Pandas) – Query ( ) method using ‘AND’ and ‘OR’

Python (Pandas)- To divide values in one Series/column by values in another Series/column

Python (Pandas) – Drop columns/series

Python (Pandas) – Pivoting

How to find the datatype of a column(s)/Series in Pandas (Python).

How to change datatype of a column/series in pandas (Python)

How to rename the column/series in pandas (Python)

How to find number of rows and column in pandas (Python)

how to plot multiple valuesets on Y-axis of plot – Matplotlib (python)

Python (pandas) :- .loc for slicing (part1)

Python (Pandas) :- .loc for slicing (part2)

Python (Pandas):- .loc for slicing (part 3)

Python (Pandas):- .loc for slicing (part-4)

Python(pandas):- set index/ reset index

Python (Pandas):- DatetimeIndex

Python (Pandas):- To parse a column as date while importing csv

Python (Pandas): Data Exploration and Data Transformation – Part 1

Python(Pandas): Data Exploration and Data Transformation – Part 2

Python(Pandas): Data Exploration and Data Transformation (Part 3)

Python (Pandas): Data Exploration and Data Transformation (Part 4)

Python (Pandas): Logical AND and Logical OR

Python (Pandas): isin( ) and not isin ( )

Python (Pandas): String functions in pandas

Python (Pandas): Replace method

Python (Pandas): How to handle Missing values (isna() , dropna(), fillna())

Python (Pandas) : Value Count

Python (Pandas) : How to remove Duplicate values (Keep=’first’, ‘last’, False)

Python (Pandas): Summary Statistics of numerical columns (describe(), std(), quantile(), mode() etc)

Python (Pandas): isin( ) and not isin( )

Python (Matplotlib):- Plot linegraph (part1)

Python(Matplotlib):- Adding xlabel, ylabel, title, figsize (part2)

Python(Matplotlib):- Marker size, Color, Linestyle, Linewidth etc (part3)

Python(matplotlib):- various colors, linestyles, markers in plot method (part4)

Python (Matplotlib):- xlabel, ylabel, title (part 5)

Python (Matplotlib):- To plot subplots which share same Y-axis

Twinx() – How to plot a graph with Dual Y axis and same X axis in Python (Matplotlib)

Python (Matplotlib):- Histogram

Python (matplotlib):- Bargraphs

Python (Matplotlib) :- Boxplot

Python (Matplotlib) :- Scatter Plot

Python (Matplotlib):- Customizations and style sheets in matplotlib visuals

Python (Matplotlib):- Saving Matplotlib plots or figures

Student Ratings & Reviews

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Python Essentials
By covering these foundational topics, the course equips learners with the skills to confidently write Python code and build simple programs, preparing them for more advanced programming and data-related courses.