Python Data Visualization in Malayalam | From Data Types to 12 Charts
Python ഉപയോഗിച്ച് ഏത് data-യ്ക്ക് ഏത് chart തിരഞ്ഞെടുക്കാം എന്ന് പഠിക്കാം! ഈ Malayalam beginner tutorial-ൽ data types വിശദീകരിച്ച് VS Code-ൽ Python code run ചെയ്യുകയും ഓരോ chart-ന്റെയും result വായിക്കുകയും ചെയ്യുന്നു.
Optional further reading (tagged product): Python Data Science Handbook, Second Edition, by Jake VanderPlas. It covers pandas, Matplotlib and working with data. Buying the book is not required for this free tutorial.
Affiliate disclosure: I may earn a commission from eligible purchases through the tagged product, at no extra cost to you.
Notebook, dataset and instructions:
github.com/AKSHAYPattayil/python-for-data-science…
Notebook with chart outputs:
github.com/AKSHAYPattayil/python-for-data-science…
CSV dataset:
github.com/AKSHAYPattayil/python-for-data-science…
Download all lesson files:
github.com/AKSHAYPattayil/python-for-data-science…
Extract the ZIP, open the data-visualization folder in VS Code, and keep the notebook, Python file and CSV together. The README includes installation and running instructions.
Topics: nominal, ordinal, binary, discrete and continuous variables; count plots; pie chart; histograms; ECDF; box plot; scatter plot; grouped counts; percentage stacked bars; and Pearson correlation heatmap. We also discuss missing ages, counts versus percentages, and correlation versus causation.
CHAPTERS
00:00 Introduction
00:24 Dataset and variable types
02:49 Load and inspect the dataset
05:48 Nominal category counts
06:45 Ordered passenger classes
07:34 Binary outcome counts
08:19 Survival shares: pie chart
09:31 Discrete count distribution
10:20 Continuous age distribution
11:15 Cumulative distribution
12:04 Age by class: box plot
13:25 Age and fare: scatter plot
14:22 Grouped survival counts
15:02 Within-class percentages
15:57 Correlation heatmap
17:18 Practice and closing
Continue the series:
Pandas Malayalam tutorial: youtube.com
VS Code Python setup: youtube.com
Dataset source: seaborn-data Titanic teaching dataset (891 passenger records).
github.com/mwaskom/seaborn-data/blob/master/titan…
Dataset notes and missing-value details are included in the lesson folder. This sample is not a complete list of everyone aboard the Titanic.
Narration generated using ElevenLabs, voice: Malayali chekkan.
#Python #DataVisualization #Malayalam
[en-US] Python Data Visualization in Malayalam | From Data Types to 12 Charts
Learn which chart to choose for which data using Python! This Malayalam beginner tutorial explains data types, runs Python code in VS Code, and reads the results of each chart.
Optional further reading (tagged product): Python Data Science Handbook, Second Edition, by Jake VanderPlas. It covers pandas, Matplotlib, and working with data. Buying the book is not required for this free tutorial.
Affiliate disclosure: I may earn a commission from eligible purchases through the tagged product, at no extra cost to you.
Notebook, dataset and instructions:
github.com/AKSHAYPattayil/python-for-data-science…
Notebook with chart outputs:
github.com/AKSHAYPattayil/python-for-data-science…
CSV dataset:
github.com/AKSHAYPattayil/python-for-data-science…
Download all lesson files:
github.com/AKSHAYPattayil/python-for-data-science…
Extract the ZIP, open the data-visualization folder in VS Code, and keep the notebook, Python file and CSV together. The README includes installation and running instructions.
Topics: nominal, ordinal, binary, discrete and continuous variables; count plots; pie chart; histograms; ECDF; box plot; scatter plot; grouped counts; percentage stacked bars; and Pearson correlation heatmap. We also discuss missing ages, counts versus percentages, and correlation versus causation.
CHAPTERS
00:00 Introduction
00:24 Dataset and variable types
02:49 Load and inspect the dataset
05:48 Nominal category counts
06:45 Ordered passenger classes
07:34 Binary outcome counts
08:19 Survival shares: pie chart
09:31 Discrete count distribution
10:20 Continuous age distribution
11:15 Cumulative distribution
12:04 Age by class: box plot
13:25 Age and fare: scatter plot
14:22 Grouped survival counts
15:02 Within-class percentages
15:57 Correlation heatmap
17:18 Practice and closing
Continue the series:
Pandas Malayalam tutorial: youtube.com
VS Code Python setup: youtube.com
Dataset source: seaborn-data Titanic teaching dataset (891 passenger records).
github.com/mwaskom/seaborn-data/blob/master/titan…
Dataset notes and missing-value details are included in the lesson folder. This sample is not a complete list of everyone aboard the Titanic.
Narration generated using ElevenLabs, voice: Malayali chekkan.
#Python #DataVisualization #Malayalam
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Python Data Visualization in Malayalam | From Data Types to 12 Charts Python ഉപയോഗിച്ച് ഏത് data-യ്ക്ക് ഏത് chart തിരഞ്ഞെടുക്കാം എന്ന് പഠിക്കാം! ഈ Malayalam beginner tutorial-ൽ data types വിശദീകരിച്ച് VS Code-ൽ Python code run ചെയ്യുകയും ഓരോ chart-ന്റെയും result വായിക്കുകയും ചെയ്യുന്നു. Optional further reading (tagged product): Python Data Science Handbook, Second Edition, by Jake VanderPlas. It covers pandas, Matplotlib and working with data. Buying the book is not required for this free tutorial. Affiliate disclosure: I may earn a commission from eligible purchases through the tagged product, at no extra cost to you. Notebook, dataset and instructions: github.com/AKSHAYPattayil/python-for-data-science… Notebook with chart outputs: github.com/AKSHAYPattayil/python-for-data-science… CSV dataset: github.com/AKSHAYPattayil/python-for-data-science… Download all lesson files: github.com/AKSHAYPattayil/python-for-data-science… Extract the ZIP, open the data-visualization folder in VS Code, and keep the notebook, Python file and CSV together. The README includes installation and running instructions. Topics: nominal, ordinal, binary, discrete and continuous variables; count plots; pie chart; histograms; ECDF; box plot; scatter plot; grouped counts; percentage stacked bars; and Pearson correlation heatmap. We also discuss missing ages, counts versus percentages, and correlation versus causation. CHAPTERS 00:00 Introduction 00:24 Dataset and variable types 02:49 Load and inspect the dataset 05:48 Nominal category counts 06:45 Ordered passenger classes 07:34 Binary outcome counts 08:19 Survival shares: pie chart 09:31 Discrete count distribution 10:20 Continuous age distribution 11:15 Cumulative distribution 12:04 Age by class: box plot 13:25 Age and fare: scatter plot 14:22 Grouped survival counts 15:02 Within-class percentages 15:57 Correlation heatmap 17:18 Practice and closing Continue the series: Pandas Malayalam tutorial: youtube.com VS Code Python setup: youtube.com Dataset source: seaborn-data Titanic teaching dataset (891 passenger records). github.com/mwaskom/seaborn-data/blob/master/titan… Dataset notes and missing-value details are included in the lesson folder. This sample is not a complete list of everyone aboard the Titanic. Narration generated using ElevenLabs, voice: Malayali chekkan. #Python #DataVisualization #Malayalam [en-US] Python Data Visualization in Malayalam | From Data Types to 12 Charts Learn which chart to choose for which data using Python! This Malayalam beginner tutorial explains data types, runs Python code in VS Code, and reads the results of each chart. Optional further reading (tagged product): Python Data Science Handbook, Second Edition, by Jake VanderPlas. It covers pandas, Matplotlib, and working with data. Buying the book is not required for this free tutorial. Affiliate disclosure: I may earn a commission from eligible purchases through the tagged product, at no extra cost to you. Notebook, dataset and instructions: github.com/AKSHAYPattayil/python-for-data-science… Notebook with chart outputs: github.com/AKSHAYPattayil/python-for-data-science… CSV dataset: github.com/AKSHAYPattayil/python-for-data-science… Download all lesson files: github.com/AKSHAYPattayil/python-for-data-science… Extract the ZIP, open the data-visualization folder in VS Code, and keep the notebook, Python file and CSV together. The README includes installation and running instructions. Topics: nominal, ordinal, binary, discrete and continuous variables; count plots; pie chart; histograms; ECDF; box plot; scatter plot; grouped counts; percentage stacked bars; and Pearson correlation heatmap. We also discuss missing ages, counts versus percentages, and correlation versus causation. CHAPTERS 00:00 Introduction 00:24 Dataset and variable types 02:49 Load and inspect the dataset 05:48 Nominal category counts 06:45 Ordered passenger classes 07:34 Binary outcome counts 08:19 Survival shares: pie chart 09:31 Discrete count distribution 10:20 Continuous age distribution 11:15 Cumulative distribution 12:04 Age by class: box plot 13:25 Age and fare: scatter plot 14:22 Grouped survival counts 15:02 Within-class percentages 15:57 Correlation heatmap 17:18 Practice and closing Continue the series: Pandas Malayalam tutorial: youtube.com VS Code Python setup: youtube.com Dataset source: seaborn-data Titanic teaching dataset (891 passenger records). github.com/mwaskom/seaborn-data/blob/master/titan… Dataset notes and missing-value details are included in the lesson folder. This sample is not a complete list of everyone aboard the Titanic. Narration generated using ElevenLabs, voice: Malayali chekkan. #Python #DataVisualization #Malayalam