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Statistics Using Python Part 5 | Data Visualization Using Matplotlib | Data Science Tutorial #5
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Statistics Using Python Part 5 | Data Visualization Using Matplotlib | Data Science Tutorial #5
Hello and welcome back to Statistics tutorials with python part 5 powered by Acadgild. In this Data science tutorial, you will be able to learn Data visualization in python using matplotlib, before that if you have missed the previous session, please go through the following links for the same.
Although the library matplotlib is the comprehensive library, in this session we will be limited to some of the common plots for visualizing the distribution.
• Scatter Plot: Scatter plot is a 2-dimensional data visualization that uses the dot to represent the value obtained from the different variables. One variable is plotted in the X-axis whereas the other one in the Y-axis.
Scatter plots are usually used when we want to show the relation between 2 variables.
Check out the hands-on example on the jupyter notebook in the video.
• Bar Plot: Bar plot shows the relationship between the numerical variable and categorical variable. Kindly go through the execution part on jupyter notebook.
• Pie Chart: Pie chart divides the circle into multiple slices that are proportional to the contribution towards the total some.
• Box Plot: In a box plot, quartiles are needling marked using rectangles. We can go ahead and see the range of the data, we can see the 1st quartile, 2nd Quartile, and upper and lower limit of the dataset.
• Histogram: Histogram is a plot that lets you discover the underline frequency distribution of a continuous data.
Kindly, go through all the plots and execution part to learn in detail. Please, subscribe and stay tuned for more such videos.
#statistics, #python, #acadgild, #datascience
For more updates on courses and tips follow us on:
Hello and welcome back to Statistics tutorials with python part 5 powered by Acadgild. In this Data science tutorial, you will be able to learn Data visualization in python using matplotlib, before that if you have missed the previous session, please go through the following links for the same.
Although the library matplotlib is the comprehensive library, in this session we will be limited to some of the common plots for visualizing the distribution.
• Scatter Plot: Scatter plot is a 2-dimensional data visualization that uses the dot to represent the value obtained from the different variables. One variable is plotted in the X-axis whereas the other one in the Y-axis.
Scatter plots are usually used when we want to show the relation between 2 variables.
Check out the hands-on example on the jupyter notebook in the video.
• Bar Plot: Bar plot shows the relationship between the numerical variable and categorical variable. Kindly go through the execution part on jupyter notebook.
• Pie Chart: Pie chart divides the circle into multiple slices that are proportional to the contribution towards the total some.
• Box Plot: In a box plot, quartiles are needling marked using rectangles. We can go ahead and see the range of the data, we can see the 1st quartile, 2nd Quartile, and upper and lower limit of the dataset.
• Histogram: Histogram is a plot that lets you discover the underline frequency distribution of a continuous data.
Kindly, go through all the plots and execution part to learn in detail. Please, subscribe and stay tuned for more such videos.
#statistics, #python, #acadgild, #datascience
For more updates on courses and tips follow us on:
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