Pandas dataframe and Seaborn for bar chat and box plot visualizations
Bar chart by using pandas and seaborn libraries:
In comparison to what we saw to create bar chart by using NumPy, Pandas, and Matplotlib, Seaborn library is used in this section to show how this Python bindings makes the visualization more easy and accessible. In this section, we use a pre-defined available dataset to show the capability of Seaborn but all of these functionalities could be used for custom datasets as well. First we load the dataset into a Pandas dataframe that shows the number of death and survivors in Titanic. Then we plot the categorized information based on sex of the survivors in each class:
Another visualization to compare the fare that is paid by passengers of Titanic in each class based on the fact that if they survived or not is shown here based on this code:
As you see all of these commands or close to English language and are self-explanatory. The final visualization of this comparison is shown here:
The bar chart that shows this visualization:
Box plots by using seaborn and pandas libraries:
Similar to the previous section, here we will use tips dataset that shows amount of tips received by waiters or waitresses during different days of the week. First we load the tips dataset into a Pandas dataframe by using:
'tips = sns.load_dataset("tips")'
Then we could plot the box plot of amount of tips in different days of the week based on gender category as:
The final notebook of these visualizations in this section is shared here: https://colab.research.google.com/drive/1v01lCb0bbKnm7SO87ju92hpiWQQBRQYP?usp=sharing
