Course
Analyzing Police Activity with pandas
IntermediateSkill Level
Updated 09/2024PythonData Manipulation4 hr16 videos50 Exercises4,100 XP66,096Statement of Accomplishment
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Prerequisites
Joining Data with pandas1
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.
2
Exploring the relationship between gender and policing
Does the gender of a driver have an impact on police behavior during a traffic stop? In this chapter, you will explore that question while practicing filtering, grouping, method chaining, Boolean math, string methods, and more!
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.
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.
Analyzing Police Activity with pandas
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FAQs
What dataset does this course use for analysis?
You analyze the Stanford Open Policing Project dataset, a real-world collection of traffic stop records, to explore how gender relates to police behavior during stops.
Is this course suitable if I just finished learning basic pandas?
It is designed for learners who already know pandas fundamentals. You should be comfortable with filtering, grouping, and joining DataFrames before starting.
What data cleaning skills will I practice in this course?
You will practice fixing data types, handling missing values, and dropping unnecessary columns and rows as part of preparing messy real-world data for analysis.
Does the course include data visualization?
Yes. Chapter 3 focuses on visual exploratory data analysis, using plots to identify trends in arrest timing and drug-related stop frequencies that raw data alone cannot reveal.
Will I work with multiple datasets or just one?
You work with two datasets. A second weather dataset is introduced in Chapter 4, which you merge with the policing data to study how weather conditions affect police behavior.
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