Udemy The (2024) Pandas Bootcamp Advanced Data Analysis with Python - Printable Version +- Softwarez.Info - Software's World! (https://softwarez.info) +-- Forum: Library Zone (https://softwarez.info/Forum-Library-Zone) +--- Forum: Video Tutorials (https://softwarez.info/Forum-Video-Tutorials) +--- Thread: Udemy The (2024) Pandas Bootcamp Advanced Data Analysis with Python (/Thread-Udemy-The-2024-Pandas-Bootcamp-Advanced-Data-Analysis-with-Python) |
Udemy The (2024) Pandas Bootcamp Advanced Data Analysis with Python - AD-TEAM - 10-27-2024 5.94 GB | 00:15:51 | mp4 | 1280X720 | 16:9 Genre:eLearning |Language:English
Files Included :
1 -Welcome to the Course! (53.79 MB) 1 -Grouping and Aggregation 101 (93.69 MB) 2 -Applying Multiple Aggregations (69.77 MB) 3 -Grouping By Multiple Columns (48.35 MB) 4 -The `transform` Method (79.41 MB) 5 -Pythonic Pivot Tables (107.69 MB) 1 -`upper`, `lower`, and `capitalize` (47.42 MB) 2 -The `len` Method (29.11 MB) 3 -Regular Expressions 101 (64.81 MB) 4 -Matching Digits with Regular Expressions (26.03 MB) 5 -The `contains` Method (97.56 MB) 6 -The `replace` Method I (59.09 MB) 7 -The `replace` Method II (62.65 MB) 1 -Using Datetime Values as Criteria (103.13 MB) 2 -The `datetime` Module I (60.68 MB) 3 -The `datetime` Module II (40.09 MB) 4 -Date Math in Pandas (88.97 MB) 5 -The `shift` Method I (90.73 MB) 6 -The `shift` Method II (45.19 MB) 7 -Calculating `rolling` Averages (73.39 MB) 1 -Data Visualization 101 1 (65.88 MB) 2 -Data Visualization 101 2 (21.25 MB) 3 -Bar Plots (45.85 MB) 4 -Scatter Plots (63.71 MB) 5 -Customizing Plot Appearance (31.97 MB) 6 -Customizing Plot Axes (59.65 MB) 1 -Apply-ing Functions to Data Analysis (19.65 MB) 2 -If Statements in Python (23.36 MB) 3 -Incorporating Multiple Logical Conditions (33.91 MB) 4 -Incorporating And and Or Logic (42.24 MB) 5 -Functions in Python (27.45 MB) 6 -Returning Values From Functions I (25.27 MB) 7 -Returning Values From Functions II (33.28 MB) 1 -The `map` Method (38.53 MB) 2 -Using `map` with Custom Functions I (54.66 MB) 3 -Using `map` with Custom Functions II (72.23 MB) 4 -The `apply` Method (61.98 MB) 5 -Applying `apply` to Multiple Columns (43.31 MB) 1 -What Is Programming (23.51 MB) 10 -Comments (17.13 MB) 11 -Text Cells (83.05 MB) 12 -Colab Tips and Pitfalls (53.18 MB) 13 -Objects, Attributes, and Methods (35.87 MB) 14 -Modules and Libraries (42.87 MB) 15 -Lists (36.2 MB) 16 -Tuples (36.15 MB) 17 -Dictionaries (54.94 MB) 2 -The Programming Environment (51.23 MB) 3 -Values and Types (26.62 MB) 4 -Functions (32.72 MB) 5 -Expressions (26.02 MB) 6 -Expressions in Colab (12.92 MB) 7 -Variables (43.35 MB) 8 -Naming Variables (21.73 MB) 9 -Errors (17.66 MB) 1 -Introducing DataFrames (44.25 MB) 10 -Selecting Columns (24.31 MB) 2 -Introducing the Example Datasets (37.74 MB) 3 -DataFrames and the `read csv` Method - Part I (99.97 MB) 4 -DataFrames and the `read csv` Method - Part II (31.56 MB) 5 -Providing DataFrame Column Names (39.32 MB) 6 -Inspecting DataFrames (53.73 MB) 7 -Data Types and the `info` Method (65.37 MB) 8 -Renaming Columns (44.79 MB) 9 -Dropping Columns (45.64 MB) 1 -Series 101 (48.25 MB) 2 -Converting Series with `to numeric` (53.56 MB) 3 -Converting Series with `to datetime` (39.05 MB) 4 -Adding Columns (Series) to DataFrames (61.05 MB) 5 -Creating Derived Columns (92.02 MB) 6 -The `assign` Method (85 MB) 1 -The `sum` Method (80.3 MB) 2 -The `count` Method (48.15 MB) 3 -Mean and Median (57.13 MB) 4 -Standard Deviation and the `describe` Method (68.6 MB) 5 -Using `describe` on Non-Numeric Fields (59.33 MB) 6 -The `unique` and `nunique` Methods (44.2 MB) 7 -The `value counts` Method (24.8 MB) 1 -The `iloc` Method (70.36 MB) 2 -Indexing Basics (80.9 MB) 3 -The `loc` Method (33.59 MB) 4 -Sorting by Index (75.75 MB) 5 -Sorting By Columns (126.03 MB) 6 -Dropping Rows By Index (73.55 MB) 1 -Filtering DataFrames with a Boolean Series (55.49 MB) 2 -Applying Other Logical Conditions (60.8 MB) 3 -The `between` and `isin` Methods (67.09 MB) 4 -Combining Conditions Using the `&` Operator (125.81 MB) 5 -Combining Conditions Using the `` Operator (40.6 MB) 6 -Combining 'And' & 'Or' Logic (122.39 MB) 7 -Negation (74.49 MB) 8 -The `isna` Method (98.84 MB) 1 -Updating DataFrame Values with `loc` (40.71 MB) 2 -Replacing DataFrame Values (48.93 MB) 3 -Updating Values with Boolean Masks (86.19 MB) 4 -Removing Null Values (93.58 MB) 5 -Replacing Null Values (61.57 MB) 6 -Identifying Duplicate Data (57.87 MB) 7 -Removing Duplicate Data (61 MB) 1 -Stacking Datasets Vertically I (53.93 MB) 2 -Stacking Datasets Vertically II (52.99 MB) 3 -Fetching Excel Data Into Pandas (63.21 MB) 4 -Joining DataFrames Horizontally I (49.94 MB) 5 -Joining DataFrames Horizontally II (75.81 MB) 6 -Left and Right Joins (81.38 MB) 7 -Full Outer Joins (52.19 MB) 8 -Combining More Than Two Tables (72.18 MB)
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