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Python for Data Science: Identifying Email Threats

Plot The Target DistributionPlot The Target Distribution

Plotting bar charts, also known as bar plots, is a useful way to visualize data and gain insights from it.

Bar charts are a simple and effective way to compare the relative sizes of different groups or categories of data. By using different colors or patterns, it becomes easy to compare the size of each group and understand the distribution of the data.

Bar charts are also useful for identifying patterns or trends in the data. For example, if the bars are sorted in a certain order, it can be used to identify if there is any correlation between different variables.

Bar charts are also useful for displaying data in a way that is easy to understand. They are simple and easy to read, even for people with little experience in data analysis.

In addition, bar charts are also useful for displaying data in a way that is easy to compare. It is possible to compare data from different groups and also compare a single group at different points in time.

Overall, bar plots are a powerful tool for visualizing data, making it easier to understand and interpret the information. They are a great way to quickly identify patterns, trends, and outliers in the data, making it easier to understand and make decisions based on it.

Task

  1. Import matplotlib and seaborn;
  2. Build the countplot of the label column from the df DataFrame.

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Section 1. Chapter 5