| 1 - Introduction to Data Visualization.mp4 | 7.2 MB | ||
| 10 - Creating Area Chart.mp4 | 35.1 MB | ||
| 11 - Creating Circle Views and SidebySide Circles.mp4 | 41.5 MB | ||
| 12 - Creating Scatter Plots.mp4 | 41.9 MB | ||
| 13 - Creating Pie Chart.mp4 | 45.8 MB | ||
| 14 - Creating histogram.mp4 | 15.6 MB | ||
| 15 - Creating text tables and highlight tables.mp4 | 6.7 MB | ||
| 16 - Creating Maps.mp4 | 40.3 MB | ||
| 17 - Creating Heat Maps.mp4 | 28.1 MB | ||
| 18 - Creating Dashboards with Tableau using Olympic Athletes Data Set.mp4 | 172.4 MB | ||
| 18 - Olympic-Athletes.xlsx | 595.7 KB | ||
| 19 - Introduction to Matplotlib.mp4 | 6.9 MB | ||
| 2 - Getting Started with Tableau Software.mp4 | 33.6 MB | ||
| 20 - Creating Line Graph.mp4 | 34.9 MB | ||
| 21 - Creating Bar Graph.mp4 | 19.5 MB | ||
| 22 - Creating Scatter Graph.mp4 | 8.7 MB | ||
| 23 - Creating Histogram Graph.mp4 | 15 MB | ||
| 24 - Creating Pie Chart.mp4 | 17.1 MB | ||
| 25 - Creating 3D plot.mp4 | 9.5 MB | ||
| 26 - Creating 3D Line graph.mp4 | 3.9 MB | ||
| 27 - Introduction to Seaborn.mp4 | 37.2 MB | ||
| 28 - Understanding Data Set.mp4 | 28.3 MB | ||
| 29 - Creating Swarm Plot.mp4 | 51.7 MB | ||
| 3 - Connecting to Data Sources Text File.mp4 | 37.3 MB | ||
| 30 - Creating Violin Plot.mp4 | 23.2 MB | ||
| 31 - Creating Facet Grids.mp4 | 59.8 MB | ||
| 32 - Creating Heatmaps.mp4 | 23.6 MB | ||
| 4 - Connecting to Data Sources EXCEL.mp4 | 17.2 MB | ||
| 5 - Creating Basic Visualizations in Tableau.mp4 | 48.7 MB | ||
| 6 - Formatting Sheets in Tableau.mp4 | 19.9 MB | ||
| 7 - Joining two tables and Creating Bar Chart.mp4 | 28.3 MB | ||
| 8 - Creating different types of Bar Charts.mp4 | 43.9 MB | ||
| 9 - Creating Line Chart.mp4 | 31.5 MB | ||
| Bonus Resources.txt | 409.6 B | ||
| Get Bonus Downloads Here.url | 204.8 B | ||
| ▲ 35 total files | |||
2023 Data Visualization In Tableau & Python (2 Courses In 1)
https://DevCourseWeb.com
Published 5/2023
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.01 GB | Duration: 1h 57m
Learn Data Visualization with Tableau & Python from the basic to advanced level using Real-Life Projects
What you'll learn
Understanding the principles of data visualization
Proficiency in Tableau
Data preparation and manipulation
Creating static visualizations with Matplotlib
Exploratory data analysis with Seaborn
Designing interactive visualizations
Visual storytelling and communication
Critically evaluating visualizations
Project-based learning
Requirements
Proficiency in Python: Since Matplotlib and Seaborn are Python libraries, a solid understanding of Python programming is necessary. Students should have a good grasp of Python syntax, variables, data structures (such as lists, dictionaries, and arrays), control flow (loops and conditionals), functions, and file I/O operations.
Knowledge of data manipulation: It is beneficial to have some experience with data manipulation and cleaning techniques, such as loading data from different file formats (CSV, Excel, etc.), handling missing values, and performing basic data transformations (filtering, grouping, merging, etc.). This can be achieved through libraries like pandas.
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