Python Plots: Matplotlib, Pyplot, Seaborn Tutorial for Beginners

Pubblicato il: 04 luglio 2021
sul canale di: Ave Coders

166

Ave Coders!
In this video, we will look at how you can represent our data graphically.
We will cover the most popular plots such as scatter plots, histograms, heatmaps, violin plots, kernel density plots, barplots, and so on.

Github:
https://github.com/AveCoders/PythonPl...

Time-stamps:
0:00 matplotlib.pyplot, seaborn
0:28 %matplotlib inline
0:55 working with csv tables (Comma Separated Values)
1:05 dataset repositories: UCI, Center for Machine Learning and Intelligent Systems
2:02 csv-table, read_csv(), head() (first 5 records)
2:33 df.info() - basic stats
3:00 picking records to plot
4:13 plt.plot() basic plot
5:28 plt.style.available - checking on styles
7:30 colors
9:40 importing table from github
12:33 matplotlib - Matlab-style, OOP-style
13:15 plt.xlim
13:35 xlabel, ylabel , title, fontsize
14:16 xticks, yticks(fontsize)
14:30 OOP-style: fig, axes = plt.subplots(nrows = 1, ncons = 1)
16:24 grids Matlab-style
17:20 grid OOP-style
18:00 style.use setting grid style:seaborn
18:25 legend Matlab-style
19:43 legend OOP-style
20:11 classic legend
20:50 plt.savefig saving plot to .png file
21:23 plt.tight_layout()
22:05 wisconsinBreastCanser.csv.
23:23 plt.boxplot
26:51 boxplot seaborn
27:38 Scatter Plot: plt.scatter(), plt.show()
28:31 Bar plot: plt.bar()
29:05 Pie chart: plt.pie() пирог
30:07 Histograms: plt.hist()
30:47 Subplots: plt.subplots
31:28 Kernel Density Plots: sns.kdeplot()
32:55 Violin Plots: sns.violinplot()
34:07 Heatmaps: sns.heatmap()

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