DATA C8
University Of California - Berkeley
Here are the best resources to pass DATA C8. Find DATA C8 study guides, notes, assignments, and much more.
9 results
Exam (elaborations)
Data C8 Lab 2: Data Types | Spring 2025, Complete Solutions
Data C8 Lab 2: Data Types | Spring 2025, Complete Solutions
Exam (elaborations)
Data C8 Lab 1: Expressions | Spring 2025, Complete Solutions
PopularData C8 Lab 1: Expressions | Spring 2025, Complete Solutions
Summary
Lab01 - Foundations of Data Science: Expressions & Python 
Basics
Lab01 - Foundations of Data Science: Expressions & Python 
Basics 
Expressions 
. You can’t learn technical subjects without hands-on practice, so labs are an important part of the course. 
Before we get started, there are some administrative details. 
The weekly lab session has two components: questions and discussion (not using the computer) about 
recent material, and a lab assignment (like this one!) that develops skills with computational and inferential 
concepts. These lab assign...
Package deal
DATA C8 LAB 1-6 PACKAGE | UNIVERSITY OF CALIFORNIA, BERKELEY
DATA C8 LAB 1-6 PACKAGE | UNIVERSITY OF CALIFORNIA, BERKELEY
Exam (elaborations)
Data C8 Lab 6: Examining the Therapeutic Touch | Spring 2025, Complete Solutions
Data C8 Lab 6: Examining the Therapeutic Touch | Spring 2025, Complete Solutions
Exam (elaborations)
Data C8 Lab 5: Simulations | Spring 2025, Complete Solutions
Data C8 Lab 5: Simulations | Spring 2025, Complete Solutions
Exam (elaborations)
Data C8 Lab 4: Functions and Visualizations | Spring 2025, Complete Solutions
Data C8 Lab 4: Functions and Visualizations | Spring 2025, Complete Solutions
Exam (elaborations)
Data C8 Lab 3: Tables | Spring 2025, Complete Solutions
Data C8 Lab 3: Tables | Spring 2025, Complete Solutions
Exam (elaborations)
Data 8 Lab 4 DATA C8|everything you need
Functions and Visualizations 
Welcome to lab 4! This week, we'll learn about functions and the table method apply from Section 8.1 
(
about visualization from Chapter 7 (
First, set up the tests and imports by running the cell below. 
In [1]: import numpy as np 
from datascience import * 
# These lines set up graphing capabilities. 
import matplotlib 
%matplotlib inline 
import t as plt 
('fivethirtyeight') 
import warnings 
efilter('ignore', FutureWarning) 
from ipywidgets import interact,...