Seaborn Tutorial
Function Reference
Seaborn Useful Resources
Selected Reading
- Seaborn - Pair Grid
- Seaborn - Facet Grid
- Seaborn - Linear Relationships
- Multi Panel Categorical Plots
- Seaborn - Plotting Wide Form Data
- Seaborn - Statistical Estimation
- Distribution of Observations
- Seaborn - Plotting Categorical Data
- Visualizing Pairwise Relationship
- Seaborn - Kernel Density Estimates
- Seaborn - Histogram
- Seaborn- Color Palette
- Seaborn - Figure Aesthetic
- Importing Datasets and Libraries
- Seaborn - Environment Setup
- Seaborn - Introduction
- Seaborn - Home
Function Reference
Seaborn Useful Resources
Selected Reading
- Who is Who
- Computer Glossary
- HR Interview Questions
- Effective Resume Writing
- Questions and Answers
- UPSC IAS Exams Notes
Seaborn - Histogram
Seaborn - Histogram
Histograms represent the data distribution by forming bins along the range of the data and then drawing bars to show the number of observations that fall in each bin.
Seaborn comes with some datasets and we have used few datasets in our previous chapters. We have learnt how to load the dataset and how to lookup the pst of available datasets.
Seaborn comes with some datasets and we have used few datasets in our previous chapters. We have learnt how to load the dataset and how to lookup the pst of available datasets.
Example
import pandas as pd import seaborn as sb from matplotpb import pyplot as plt df = sb.load_dataset( iris ) sb.distplot(df[ petal_length ],kde = False) plt.show()
Output
Here, kde flag is set to False. As a result, the representation of the kernel estimation plot will be removed and only histogram is plotted.
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