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[ DevCourseWeb com ] Udemy - Python for Data Analysis and Visualization 2022
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1. Course Welcome & Set Up
1. Course Overview.mp4
1. Course Overview.srt
2. Udemy 101.html
3. Python Overview.mp4
3. Python Overview.srt
4. Anaconda Distribution Installation.mp4
4. Anaconda Distribution Installation.srt
5. Jupyter Notebook 101.mp4
5. Jupyter Notebook 101.srt
6. Jupyter Notebook - Adding Comments in Cells.mp4
6. Jupyter Notebook - Adding Comments in Cells.srt
7. Course Resources - Important!.mp4
7. Course Resources - Important!.srt
Course Resurces-Python for Data Analysis and Visualization
02 Objects Variables and Data Types
01 Objects and Variables
DS_Store
objects_variables.ipynb
02 Numbers
DS_Store
numbers.ipynb
03 Strings
DS_Store
strings.ipynb
04 String Operations
DS_Store
string_operations.ipynb
05 String Methods
DS_Store
string_methods.ipynb
06 String Concat and Formatting
DS_Store
string_concat_and_formatting.ipynb
07 Lists
DS_Store
lists.ipynb
08 Dictionaries
DS_Store
dictionaries.ipynb
09 Tuples and Sets
DS_Store
tuples_and_sets.ipynb
10 Booleans
DS_Store
booleans.ipynb
DS_Store
03 Control Flow and Loops
01 Python Operators
DS_Store
python_operators.ipynb
02 if-elif-else
DS_Store
if_elif_else.ipynb
03 For Loops
DS_Store
for_loops.ipynb
04 For Loops Continued
DS_Store
for_loops_continued.ipynb
05 While Loops
DS_Store
while_loops.ipynb
06 Break Continue Pass
DS_Store
break_continue_pass.ipynb
07 List Comprehension
DS_Store
list_comprehension.ipynb
DS_Store
04 Functions
01 Built In Functions
DS_Store
built-in_functions.ipynb
02 User Defined Functions
DS_Store
user_defined_functions.ipynb
03 User Defined Functions Examples
DS_Store
examples.ipynb
05 Map and Filter
DS_Store
map_and_filter.ipynb
06 Lamdba Functions
DS_Store
lambda_functions.ipynb
07 Error and Exception Handling
DS_Store
error_and_exception_handling.ipynb
DS_Store
05 Challenge Section - Core Python
DS_Store
challenge_questions_core_python.ipynb
challenge_questions_core_python_SOLUTIONS.ipynb
07 NumPy
1 NumPy Overview
DS_Store
numpy_overview.ipynb
2 Array Slicing and Indexing
DS_Store
array_indexing_and_slicing.ipynb
3 Array Manipulation Functions
DS_Store
array_manipulation_functions.ipynb
4 Additional Array Creation Functions
DS_Store
array_creation_functions.ipynb
5 Array Mathematics
DS_Store
array_mathematics.ipynb
6 IO Functions
DS_Store
io_functions.ipynb
tfl-daily-cycle-hires.csv
tfl-daily-cycle-hires.txt
DS_Store
08 Challenge Section - NumPy
DS_Store
challenge_questions_numpy.ipynb
challenge_questions_numpy_SOLUTIONS.ipynb
tfl-daily-cycle-hires-2018.csv
tfl-daily-cycle-hires-2019.csv
09 Pandas
02 Introduction to Series
DS_Store
introduction_to_series.ipynb
03 Introduction to DataFrames
DS_Store
introduction_to_dataframes.ipynb
top_10_countries.csv
top_10_countries_no_header.csv
04 Selecting Data 1
DS_Store
selecting_data_1.ipynb
top_10_countries.csv
05 Selecting Data 2
DS_Store
selecting_data_2.ipynb
top_10_countries.csv
06 Data Manipulation 1
DS_Store
data_manipulation_1.ipynb
top_10_countries.csv
07 Data Manipulation 2
DS_Store
data_manipulation_2.ipynb
tfl-daily-cycle-hires.csv
08 Data Aggregation and Grouping
DS_Store
data_aggregation_and_grouping.ipynb
top_10_countries.csv
09 Data Cleansing
DS_Store
data_cleansing.ipynb
10 Combining DataFrames
DS_Store
combining_dataframes.ipynb
employees_hr.xls
11 Windowing Operations
DS_Store
tfl-daily-cycle-hires.csv
windowing_operations.ipynb
DS_Store
10 Challenge Section - Pandas
1 TfL Dataset Challenge
DS_Store
challenge_questions_tfl.ipynb
challenge_questions_tfl_SOLUTIONS.ipynb
tfl-daily-cycle-hires.csv
2 Employees Dataset Challenge
DS_Store
challenge_questions_employees.ipynb
challenge_questions_employees_SOLUTIONS.ipynb
departments.csv
employees.csv
salaries.csv
DS_Store
11 Data Sources
01 Excel and CSV
DS_Store
excel_and_csv.ipynb
top_10_countries.csv
top_10_countries.xls
02 HTML
DS_Store
html.ipynb
DS_Store
12 Matplotlib
03 Creating a Plot Area 1
DS_Store
creating_a_plot_area_1.ipynb
04 Creating a Plot Area 2
DS_Store
creating_a_plot_area_2.ipynb
05 Bar Plots
DS_Store
bar_plots.ipynb
top_10_countries.csv
06 Line Plots
DS_Store
line_plots.ipynb
tfl-daily-cycle-hires.csv
07 Scatter Plots
DS_Store
players_21.csv
scatter_plots.ipynb
08 Histograms
DS_Store
histograms.ipynb
players_21.csv
09 Box Plots and Violin Plots
DS_Store
box_plots_and_violin_plots.ipynb
players_21.csv
10 Style and Presentation
DS_Store
style_and_presentation.ipynb
11 Additional Resources and Cheat Sheets
DS_Store
cheatsheets-1.webp
cheatsheets-2.webp
handout-beginner.pdf
handout-intermediate.pdf
handout-tips.pdf
DS_Store
13 Challenge Section - Matplotlib
DS_Store
challenge_questions_matplotlib.ipynb
challenge_questions_matplotlib_SOLUTIONS.ipynb
tfl-daily-cycle-hires.csv
14 Seaborn
02 Categorical Plots
DS_Store
categorical_plots.ipynb
players_21_top_100.csv
top_10_countries.csv
03 Relational Plots
DS_Store
relational_plots.ipynb
stocks.xlsx
04 Distribution Plots
DS_Store
distribution_plots.ipynb
05 Regression Plots
DS_Store
regression_plots.ipynb
06 Matrix Plots
DS_Store
matrix_plots.ipynb
players_21.csv
07 Multi Plot Grids
DS_Store
multi_plot_grids.ipynb
08 Style and Presentation
DS_Store
style_and_presentation.ipynb
DS_Store
15 Challenge Section - Seaborn
DS_Store
challenge_questions_seaborn.ipynb
challenge_questions_seaborn_SOLUTIONS.ipynb
players_21.csv
DS_Store
__MACOSX
Course Resurces-Python for Data Analysis and Visualization
02 Objects Variables and Data Types
01 Objects and Variables
_.DS_Store
_objects_variables.ipynb
02 Numbers
_.DS_Store
_numbers.ipynb
03 Strings
_.DS_Store
_strings.ipynb
04 String Operations
_.DS_Store
_string_operations.ipynb
05 String Methods
_.DS_Store
_string_methods.ipynb
06 String Concat and Formatting
_.DS_Store
_string_concat_and_formatting.ipynb
07 Lists
_.DS_Store
_lists.ipynb
08 Dictionaries
_.DS_Store
_dictionaries.ipynb
09 Tuples and Sets
_.DS_Store
_tuples_and_sets.ipynb
10 Booleans
_.DS_Store
_booleans.ipynb
_.DS_Store
_01 Objects and Variables
_02 Numbers
_03 Strings
_04 String Operations
_05 String Methods
_06 String Concat and Formatting
_07 Lists
_08 Dictionaries
_09 Tuples and Sets
_10 Booleans
03 Control Flow and Loops
01 Python Operators
_.DS_Store
02 if-elif-else
_.DS_Store
03 For Loops
_.DS_Store
04 For Loops Continued
_.DS_Store
05 While Loops
_.DS_Store
06 Break Continue Pass
_.DS_Store
07 List Comprehension
_.DS_Store
_.DS_Store
_01 Python Operators
_02 if-elif-else
_03 For Loops
_04 For Loops Continued
_05 While Loops
_06 Break Continue Pass
_07 List Comprehension
04 Functions
01 Built In Functions
_.DS_Store
02 User Defined Functions
_.DS_Store
03 User Defined Functions Examples
_.DS_Store
05 Map and Filter
_.DS_Store
06 Lamdba Functions
_.DS_Store
07 Error and Exception Handling
_.DS_Store
_.DS_Store
_01 Built In Functions
_02 User Defined Functions
_03 User Defined Functions Examples
_05 Map and Filter
_06 Lamdba Functions
_07 Error and Exception Handling
05 Challenge Section - Core Python
_.DS_Store
07 NumPy
1 NumPy Overview
_.DS_Store
2 Array Slicing and Indexing
_.DS_Store
3 Array Manipulation Functions
_.DS_Store
4 Additional Array Creation Functions
_.DS_Store
5 Array Mathematics
_.DS_Store
6 IO Functions
_.DS_Store
_tfl-daily-cycle-hires.csv
_tfl-daily-cycle-hires.txt
_.DS_Store
_1 NumPy Overview
_2 Array Slicing and Indexing
_3 Array Manipulation Functions
_4 Additional Array Creation Functions
_5 Array Mathematics
_6 IO Functions
08 Challenge Section - NumPy
_.DS_Store
_tfl-daily-cycle-hires-2018.csv
_tfl-daily-cycle-hires-2019.csv
09 Pandas
02 Introduction to Series
_.DS_Store
03 Introduction to DataFrames
_.DS_Store
_top_10_countries.csv
_top_10_countries_no_header.csv
04 Selecting Data 1
_.DS_Store
_top_10_countries.csv
05 Selecting Data 2
_.DS_Store
_top_10_countries.csv
06 Data Manipulation 1
_.DS_Store
_data_manipulation_1.ipynb
_top_10_countries.csv
07 Data Manipulation 2
_.DS_Store
_data_manipulation_2.ipynb
_tfl-daily-cycle-hires.csv
08 Data Aggregation and Grouping
_.DS_Store
_data_aggregation_and_grouping.ipynb
_top_10_countries.csv
09 Data Cleansing
_.DS_Store
10 Combining DataFrames
_.DS_Store
_employees_hr.xls
11 Windowing Operations
_.DS_Store
_tfl-daily-cycle-hires.csv
_.DS_Store
_02 Introduction to Series
_03 Introduction to DataFrames
_04 Selecting Data 1
_05 Selecting Data 2
_06 Data Manipulation 1
_07 Data Manipulation 2
_08 Data Aggregation and Grouping
_09 Data Cleansing
_10 Combining DataFrames
_11 Windowing Operations
10 Challenge Section - Pandas
1 TfL Dataset Challenge
_.DS_Store
_tfl-daily-cycle-hires.csv
2 Employees Dataset Challenge
_.DS_Store
_departments.csv
_employees.csv
_salaries.csv
_.DS_Store
_1 TfL Dataset Challenge
_2 Employees Dataset Challenge
11 Data Sources
01 Excel and CSV
_.DS_Store
_top_10_countries.csv
_top_10_countries.xls
02 HTML
_.DS_Store
_.DS_Store
_01 Excel and CSV
_02 HTML
12 Matplotlib
03 Creating a Plot Area 1
_.DS_Store
04 Creating a Plot Area 2
_.DS_Store
05 Bar Plots
_.DS_Store
_top_10_countries.csv
06 Line Plots
_.DS_Store
_tfl-daily-cycle-hires.csv
07 Scatter Plots
_.DS_Store
_players_21.csv
08 Histograms
_.DS_Store
_players_21.csv
09 Box Plots and Violin Plots
_.DS_Store
_players_21.csv
10 Style and Presentation
_.DS_Store
11 Additional Resources and Cheat Sheets
_.DS_Store
_cheatsheets-1.webp
_cheatsheets-2.webp
_handout-beginner.pdf
_handout-intermediate.pdf
_handout-tips.pdf
_.DS_Store
_03 Creating a Plot Area 1
_04 Creating a Plot Area 2
_05 Bar Plots
_06 Line Plots
_07 Scatter Plots
_08 Histograms
_09 Box Plots and Violin Plots
_10 Style and Presentation
_11 Additional Resources and Cheat Sheets
13 Challenge Section - Matplotlib
_.DS_Store
_tfl-daily-cycle-hires.csv
14 Seaborn
02 Categorical Plots
_.DS_Store
_players_21_top_100.csv
_top_10_countries.csv
03 Relational Plots
_.DS_Store
_stocks.xlsx
04 Distribution Plots
_.DS_Store
05 Regression Plots
_.DS_Store
06 Matrix Plots
_.DS_Store
_players_21.csv
07 Multi Plot Grids
_.DS_Store
08 Style and Presentation
_.DS_Store
_.DS_Store
_02 Categorical Plots
_03 Relational Plots
_04 Distribution Plots
_05 Regression Plots
_06 Matrix Plots
_07 Multi Plot Grids
_08 Style and Presentation
15 Challenge Section - Seaborn
_.DS_Store
_players_21.csv
_.DS_Store
_02 Objects Variables and Data Types
_03 Control Flow and Loops
_04 Functions
_05 Challenge Section - Core Python
_06 Modules Packages and Libraries
_07 NumPy
_08 Challenge Section - NumPy
_09 Pandas
_10 Challenge Section - Pandas
_11 Data Sources
_12 Matplotlib
_13 Challenge Section - Matplotlib
_14 Seaborn
_15 Challenge Section - Seaborn
_Course Resurces-Python for Data Analysis and Visualization
10. Challenge Section - Pandas
1. Challenge Questions - TfL Dataset.mp4
1. Challenge Questions - TfL Dataset.srt
2. Solutions Walkthrough.mp4
2. Solutions Walkthrough.srt
3. Challenge Questions - Employees Dataset.mp4
3. Challenge Questions - Employees Dataset.srt
4. Solutions Walkthrough.mp4
4. Solutions Walkthrough.srt
11. Data Sources
1. Excel and CSV.mp4
1. Excel and CSV.srt
2. HTML.mp4
2. HTML.srt
3. Databases.mp4
3. Databases.srt
4. Pandas Input and Output Methods.mp4
4. Pandas Input and Output Methods.srt
12. Matplotlib
1. Matplotlib Overview.mp4
1. Matplotlib Overview.srt
10. Box Plots and Violin Plots.mp4
10. Box Plots and Violin Plots.srt
11. Style and Presentation.mp4
11. Style and Presentation.srt
12. Additional Resources and Cheat Sheets.mp4
12. Additional Resources and Cheat Sheets.srt
2. Choosing the Right Chart Type.mp4
2. Choosing the Right Chart Type.srt
3. Creating a Plot Area 1.mp4
3. Creating a Plot Area 1.srt
4. Creating a Plot Area 2.mp4
4. Creating a Plot Area 2.srt
5. Bar Plots.mp4
5. Bar Plots.srt
6. Line Plots.mp4
6. Line Plots.srt
7. FIFA 21 Player Dataset.html
8. Scatter Plots.mp4
8. Scatter Plots.srt
9. Histograms.mp4
9. Histograms.srt
13. Challenge Section - Matplotlib
1. Challenge Questions Overview.mp4
1. Challenge Questions Overview.srt
2. Solutions Walkthrough.mp4
2. Solutions Walkthrough.srt
14. Seaborn
1. Seaborn Overview.mp4
1. Seaborn Overview.srt
2. Categorical Plots.mp4
2. Categorical Plots.srt
3. Relational Plots.mp4
3. Relational Plots.srt
4. Distribution Plots.mp4
4. Distribution Plots.srt
5. Regression Plots.mp4
5. Regression Plots.srt
6. Matrix Plots.mp4
6. Matrix Plots.srt
7. Multi Plot Grids.mp4
7. Multi Plot Grids.srt
8. Style and Presentation.mp4
8. Style and Presentation.srt
15. Challenge Section - Seaborn
1. Challenge Questions Overview.mp4
1. Challenge Questions Overview.srt
2. Solutions Walkthrough.mp4
2. Solutions Walkthrough.srt
2. Objects, Variables and Data Types
1. Objects and Variables Overview.mp4
1. Objects and Variables Overview.srt
10. String Methods.html
11. String Concatenation and Formatting.mp4
11. String Concatenation and Formatting.srt
12. Lists.mp4
12. Lists.srt
13. Lists.html
14. Lists.html
15. Dictionaries.mp4
15. Dictionaries.srt
16. Dictionaries.html
17. Tuples and Sets.mp4
17. Tuples and Sets.srt
18. Tuples and Sets.html
19. Booleans.mp4
19. Booleans.srt
2. Numbers.mp4
2. Numbers.srt
20. Key Words in Python.html
21. Data Types.html
3. Integer Variables.html
4. Float Variables.html
5. Strings.mp4
5. Strings.srt
6. Print Formatting with Strings.html
7. String Operations.mp4
7. String Operations.srt
8. String Indexing and Slicing Quiz.html
9. String Methods and Properties.mp4
9. String Methods and Properties.srt
3. Control Flow and Loops
1. Python Operators.mp4
1. Python Operators.srt
10. List Comprehension.mp4
10. List Comprehension.srt
11. List Comprehension.html
12. IN and NOT IN.mp4
12. IN and NOT IN.srt
2. Control Flow.mp4
2. Control Flow.srt
3. Control Flow.html
4. For Loops.mp4
4. For Loops.srt
5. For Loops (continued).mp4
5. For Loops (continued).srt
6. For Loops.html
7. For Loops.html
8. While Loops.mp4
8. While Loops.srt
9. Break, Continue and Pass Statements.mp4
9. Break, Continue and Pass Statements.srt
4. Functions
1. Built-In Functions.mp4
1. Built-In Functions.srt
10. Lambda Functions.html
11. Errors and Exception Handling.mp4
11. Errors and Exception Handling.srt
2. Built-In Functions.html
3. User Defined Functions.mp4
3. User Defined Functions.srt
4. User Defined Functions - Examples.mp4
4. User Defined Functions - Examples.srt
5. User Defined Functions.html
6. User Defined Functions.html
7. Arguments and Keyword Arguments.mp4
7. Arguments and Keyword Arguments.srt
8. Map and Filter.mp4
8. Map and Filter.srt
9. Lambda Functions.mp4
9. Lambda Functions.srt
5. Challenge Section - Core Python
1. Challenge Questions Overview.mp4
1. Challenge Questions Overview.srt
2. Solutions Walkthrough.mp4
2. Solutions Walkthrough.srt
6. Modules, Packages and Libraries
1. Built-In Modules.mp4
1. Built-In Modules.srt
2. External Libraries.mp4
2. External Libraries.srt
7. NumPy
1. NumPy Overview.mp4
1. NumPy Overview.srt
2. Array Slicing and Indexing.mp4
2. Array Slicing and Indexing.srt
3. Array Manipulation Functions.mp4
3. Array Manipulation Functions.srt
4. Additional Array Creation Functions.mp4
4. Additional Array Creation Functions.srt
5. Array Arithmetic and Mathematical Functions.mp4
5. Array Arithmetic and Mathematical Functions.srt
6. IO Functions in NumPy.mp4
6. IO Functions in NumPy.srt
8. Challenge Section - NumPy
1. Challenge Questions.mp4
1. Challenge Questions.srt
2. Challenge Solutions.mp4
2. Challenge Solutions.srt
9. Pandas
1. Pandas Overview.mp4
1. Pandas Overview.srt
10. Combining DataFrames.mp4
10. Combining DataFrames.srt
11. Windowing Operations.mp4
11. Windowing Operations.srt
2. Introduction to Series.mp4
2. Introduction to Series.srt
3. Introduction to DataFrames.mp4
3. Introduction to DataFrames.srt
4. Selecting Data.mp4
4. Selecting Data.srt
5. Selecting Data 2.mp4
5. Selecting Data 2.srt
6. Data Manipulation 1.mp4
6. Data Manipulation 1.srt
7. Data Manipulation 2.mp4
7. Data Manipulation 2.srt
8. Data Aggregation and Grouping.mp4
8. Data Aggregation and Grouping.srt
9. Data Cleansing.mp4
9. Data Cleansing.srt
Bonus Resources.txt
Torrent description
Feel free to post any comments about this torrent, including links to Subtitle, samples, screenshots, or any other relevant information, Watch [ DevCourseWeb com ] Udemy - Python for Data Analysis and Visualization 2022 Online Free Full Movies Like 123Movies, Putlockers, Fmovies, Netflix or Download Direct via Magnet Link in Torrent Details.
