Skip to content
Intermediate Python
  • AI Chat
  • Code
  • Report

    • Intermediate Python

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

    Take Notes

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

    help(plt.hist) x should be a list of values you want to build a histogram for, bins tells python how many bins. If you dont specify then it will be 10 by default

    print () - display x[-1] retrieve data in array, it starts from 0, -1 to start from end import matplotlib.pyplot as plt

    plt.show()- display graph plt.plot(x,y) plt.scatter(x,y)

    plt.hist(values, bins)/ plt.hist(values)

    //Add labels to axis on graph plt.xlabel('Year') plt.ylabel('Popullation') plt.Title('World Population Projection') plt.yticks([0,2,4,6,8,10], [0B, 2B, 4B, 6B, 10B]) // changes the y axis to vales in billions

    year = [1800,1850,1900] + year // Adds additional data to an existing list

    plt.xscale('log') logarithmetic scale

    col - color

    alpha is opacity ranges between 0 & 1

    plt.text() plt.grid(TRUE) \ Adds gridlines

    Index ind_alb = countries.index("alabama") // Fetch index number pop[ind_alb]

    Dictionaries

    world = {"Afghan": 20.88, "Iran":20} world [albania]// Fetches data aligned in dictionary

    //Pandas is an open source library, providing high-performance, easy-to-use data structures and data analysis tools for Python.

    //The DataFrame is one of Pandas' most important data structures. It's basically a way to store tabular data where you can label the rows and the columns. One way to build a DataFrame is from a dictionary.

    cars = pd.DataFrame(cars_dict)

    Import the cars.csv data: cars

    cars = pd.DataFrame(pd.read_csv('cars.csv'))

    Fix import by including index_col

    cars = pd.read_csv('cars.csv',index_col = 0)

    brics= pd.read_csv("path/to/brics.csv",index_col = 0) // importing CSV file into dataframe as brics

    //Select specific columns in a dataframe , use double brackets and columns needed bric[["country", "capital"]]

    //select specific rows in a dataframe, use indexing/slicing bric[1:4]

    Explore Datasets

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

    • Create a loop that iterates through the brics DataFrame and prints "The population of {country} is {population} million!".
    • Create a histogram of the life expectancies for countries in Africa in the gapminder DataFrame. Make sure your plot has a title, axis labels, and has an appropriate number of bins.
    • Simulate 10 rolls of two six-sided dice. If the two dice add up to 7 or 11, print "A win!". If the two dice add up to 2, 3, or 12, print "A loss!". If the two dice add up to any other number, print "Roll again!".