Introduction to Data Science in Python
Run the hidden code cell below to import the data used in this course.
Getting Started in Python
var = 'test'Loading Data in pandas..
import pandas as pd
from matplotlib import pyplot as plt
ransom = pd.read_csv("datasets/ransom.csv")
credit_records = (pd.read_csv("datasets/credit_records.csv"))
#print(ransom)
#print(ransom.head())
print(credit_records.price.sum)1 hidden cell
Plotting data with Matplotlib
Different Types of Plots
Take Notes
Add notes about the concepts you've learned and code cells with code you want to keep.
Making a scatter plot
plt.scatter(df.age, df.height) plt.xlabel('Age (in months)') plt.ylabel('Height (in inches)') plt.show
plt.scatter(df.age, df.height, color='green', marker='s')
plt.scatter(df.x_data,
df.y_daya,
alpha=0.1)
Making a bar chart:
plt.bar(df.precint, df.pets_abducted) plt.ylabel('Pet Abductions') plt.show()
horizontal bar: plt.barh(df.precint, df.pets_abducted) plt.ylabel('Pet Abductions') plt.show()
adding error bars: plt.bar(df.precint, df.pet_abductions, yerr=df.error) plt.ylabel('Pet Abductions') plt.show()
stacked bar charts: plt.bar(df.precinct, df.dog, label='Dog') plt.bar(df.precinct, df.cat, bottom=df.dog, label='Cat') plt.legeng() plt.show()
# Add your code snippets here