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Analyzing Police Activity with pandas

Explore the Stanford Open Policing Project dataset and analyze the impact of gender on police behavior using pandas.

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4 Hours16 Videos50 Exercises52,445 Learners4100 XPData Analyst TrackData Manipulation TrackData Scientist Track

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Course Description

Now that you have learned the foundations of pandas, this course will give you the chance to apply that knowledge by answering interesting questions about a real dataset! You will explore the Stanford Open Policing Project dataset and analyze the impact of gender on police behavior. During the course, you will gain more practice cleaning messy data, creating visualizations, combining and reshaping datasets, and manipulating time series data. Analyzing Police Activity with pandas will give you valuable experience analyzing a dataset from start to finish, preparing you for your data science career!

  1. 1

    Preparing the data for analysis


    Before beginning your analysis, it is critical that you first examine and clean the dataset, to make working with it a more efficient process. In this chapter, you will practice fixing data types, handling missing values, and dropping columns and rows while learning about the Stanford Open Policing Project dataset.

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    Stanford Open Policing Project dataset
    50 xp
    Examining the dataset
    100 xp
    Dropping columns
    100 xp
    Dropping rows
    100 xp
    Using proper data types
    50 xp
    Finding an incorrect data type
    50 xp
    Fixing a data type
    100 xp
    Creating a DatetimeIndex
    50 xp
    Combining object columns
    100 xp
    Setting the index
    100 xp
  2. 3

    Visual exploratory data analysis

    Are you more likely to get arrested at a certain time of day? Are drug-related stops on the rise? In this chapter, you will answer these and other questions by analyzing the dataset visually, since plots can help you to understand trends in a way that examining the raw data cannot.

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  3. 4

    Analyzing the effect of weather on policing

    In this chapter, you will use a second dataset to explore the impact of weather conditions on police behavior during traffic stops. You will practice merging and reshaping datasets, assessing whether a data source is trustworthy, working with categorical data, and other advanced skills.

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In the following tracks

Data Analyst Data Manipulation Data Scientist


beccarobinsBecca RobinssarasnellSara Snell
Kevin Markham Headshot

Kevin Markham

Founder of Data School

Kevin is the founder of Data School, an online school for learning data science with Python. He is passionate about teaching people who are new to the field, regardless of their educational and professional backgrounds. Currently, he teaches machine learning and data analysis to over 10,000 students each month through the Data School YouTube channel. He has a degree in Computer Engineering from Vanderbilt University.
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