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Data Manipulation with pandas
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    • Data Manipulation with pandas

    Run the hidden code cell below to import the data used in this course.

    # Import the course packages
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

# Import the four datasets
avocado = pd.read_csv("datasets/avocado.csv")
homelessness = pd.read_csv("datasets/homelessness.csv")
temperatures = pd.read_csv("datasets/temperatures.csv")
walmart = pd.read_csv("datasets/walmart.csv")

    Take Notes

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

    Add your notes here

    #DataFrame.drop_duplicates
df.drop_duplicates(subset='column') #subset may be a list, it will drop duplicates of df. You may check more than one column with a list
df['column'].value_counts() #it will count each value on the column. sort=False (sort by descending order), normalize = False (normalize by the number of rows)
df.groupby('column')['column2'].agg(functions)
df.pivot_table(values='column1',index='column2',aggfunc=functions )

    Explore Datasets

    Use the DataFrames imported in the first cell to explore the data and practice your skills!

    • Print the highest weekly sales for each department in the walmart DataFrame. Limit your results to the top five departments, in descending order. If you're stuck, try reviewing this video.
    • What was the total nb_sold of organic avocados in 2017 in the avocado DataFrame? If you're stuck, try reviewing this video.
    • Create a bar plot of the total number of homeless people by region in the homelessness DataFrame. Order the bars in descending order. Bonus: create a horizontal bar chart. If you're stuck, try reviewing this video.
    • Create a line plot with two lines representing the temperatures in Toronto and Rome. Make sure to properly label your plot. Bonus: add a legend for the two lines. If you're stuck, try reviewing this video.