Course Notes: Exploratory Data Analysis in Python
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    Course Notes

    Use this workspace to take notes, store code snippets, or build your own interactive cheatsheet! The datasets used in this course are available in the datasets folder.

    # Import any packages you want to use here
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns

    Take Notes

    Add notes here about the concepts you've learned and code cells with code you want to keep.

    Add your notes here

    # Add your code snippets here
books = pd.read_csv("clean_books.csv")
unemp = pd.read_csv("clean_unemployment.csv")
divorce = pd.read_csv("ds_salaries_clean.csv")
salaries = pd.read_csv("ds_salaries_clean.csv")
    # Print the first five rows of unemployment

unemp.head()
    # Print a summary of non-missing values and data types in the unemployment DataFrame

unemp.info()
    # Print summary statistics for numerical columns in unemployment

unemp.describe().T
    # Count the values associated with each continent in unemployment
    # Create a histogram of 2021 unemployment; show a full percent in each bin
    # Update the data type of the 2019 column to a float
# Print the dtypes to check your work
    # Define a Series describing whether each continent is outside of Oceania
    # Print unemployment without records related to countries in Oceania
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