🥫HOMEWORK 1: Intro to NumPy & Pandas🥫

Questions based on Mini-Lecture 2️⃣

To work on this HW, duplicate this Notebook and edit it in your workspace!

import pandas as pd import numpy as np from datascience import *

Dataset to use: click me!

https://www.kaggle.com/datasets/ulrikthygepedersen/which-ketchup-is-best

🍅 Background info/context: I LOVE Ketchup! (who doesn't?) Unfortunately, there's too many brands out there and in this economy I can't afford to buy every bottle to taste every brand. To help me solve this personal crisis, please take a look at this survey dataset containing a survey of people's opinions on different ketchup brands, their prices, and other information!

1. NumPy #️⃣🥧

# importing dataset as a NUMPY dataframe ketchup_np = Table().read_table("Ketchup.csv") ketchup_np

##Question 1: Sort the prices of heinz ketchup in ketchup_np in ascending order, return top 10 ketchup_np = ketchup_np.sort('price.heinz', descending=True) ketchup_np.show(10)

##Question 2: Group by ketchup choice, then show only the ketchup choice and average prices of each brand q2 = ketchup_np.group('Ketchup.choice', collect=np.mean).drop(['Unnamed: 0 mean', 'Ketchup.hid mean', 'Ketchup.id mean']) q2.show()

2. Pandas!! 🐼

# importing dataset as a PANDAS dataframe ketchup_pd = pd.read_csv("Ketchup.csv") ketchup_pd

# Question 3: Select the price of the different ketchup brands. Sort in the order of: heinz, hunts, delmonte, and stb. # Hint: if you are stuck, check this out! https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.sort_values.html ketchup_pd = ketchup_pd.sort_values(by=['price.heinz', 'price.hunts', 'price.delmonte', 'price.stb']) ketchup_pd.head()

# Question 4: Find the brand chosen the most in the data frame. Your answer should output one line. # Hint: Try using .value_counts!! # Hint 2: After you have your SERIES of value counts, use a double bracket to get the first line! ketchup_pd[['Ketchup.choice']].value_counts()[[0]]

# QUESTION 5: Within the Ketchup.choice column, select all the people who chose heinz. Then sort in DESCENDING order by price. # Hint:Confused on boolean conditioning? Check this out (DATA 100 content!): https://docs.google.com/presentation/d/1EyNlu_BDGSW3TiIxPkdwC2tSBwjp-XWENpFxC3X7F8I/edit#slide=id.g8a ketchup_pd[ketchup_pd['Ketchup.choice'] == 'heinz'].sort_values(by='price.heinz').drop(['price.hunts', 'price.delmonte', 'price.stb'], axis=1)

3. Reading! 📚

Read this article: click me! Give a 5 sentence summary of the article or something that you've learned from it.

https://medium.com/@dssberkeley/behind-berkeleys-most-popular-double-major-how-applicable-is-ds-x-econ-in-industry-64ea4dcca327

Economics and Data Science are the most common double majors at UC Berkeley. However, the rise of double majors in economics is correlated with the rise of Data Science. There are many jobs that can take advantage of the skillsets from two majors. Even though the job title might be similar, the job skillsets differ depending on the fields and the companies. Additionally, communication skill is very important for anyone wanting to pursue a Data Analyst career.

🥫HOMEWORK 1: Intro to NumPy & Pandas🥫

Questions based on Mini-Lecture 2️⃣

1. NumPy #️⃣🥧

2. Pandas!! 🐼

3. Reading! 📚

Congrats!! That's it! You've just finished your first HW in the DeCal! 😃