Spreadsheets Tutorial : Organizing Rows and Columns

DataCamp · Beginner ·📊 Data Analytics & Business Intelligence ·6y ago
Want to learn more? Take the full course at https://learn.datacamp.com/courses/pivot-tables-in-spreadsheets at your own pace. More than a video, you'll learn hands-on coding & quickly apply skills to your daily work. --- In the last lesson, you learned how to create the shell of a pivot table. Now you will begin to populate the pivot table with data. While there are many options to building your pivot table, the first choice is often selecting the rows and columns. You'll start with the worksheet tab you created last time, which shows the pivot table editor on the right hand side, and a blank shell of the pivot table within your worksheet. The first thing you want to do is to select a category to go in the Rows field. When you click on Add next to the Rows section, you will see a dropdown list which contains the column headers from your source data. Now, when you select any of these categories, the pivot table will list all of the unique values found in that column of your source data. I will select Industry, and the pivot table will now show all of the industries contained in my original dataset. Now we have a list of industries for the Top 10 companies in the world. Next, you can select categories for the Columns field the same way. By clicking Add, you will see the dropdown menu containing the same list of column headers. I will select Year, and the pivot table now shows all of the years that are contained in the source data. You can select multiple rows or columns as well, by clicking Add again, and selecting another category. In the rows section, I will add the category Name so that the name of each company is listed underneath the industry. Do you see any surprises on this list? It looks like the Petroleum Refining industry is doing well, with four companies in the top ten! Please note that you can re-arrange the order of the rows by clicking and dragging the field names above or below each other. You can also click and drag them from rows to columns, o
Watch on YouTube ↗ (saves to browser)
Sign in to unlock AI tutor explanation · ⚡30

Playlist

Uploads from DataCamp · DataCamp · 0 of 60

← Previous Next →
1 SQL Server Tutorial: Date manipulation
SQL Server Tutorial: Date manipulation
DataCamp
2 R Tutorial: Intermediate Interactive Data Visualization with plotly in R
R Tutorial: Intermediate Interactive Data Visualization with plotly in R
DataCamp
3 R Tutorial: Adding aesthetics to represent a variable
R Tutorial: Adding aesthetics to represent a variable
DataCamp
4 R Tutorial: Moving Beyond Simple Interactivity
R Tutorial: Moving Beyond Simple Interactivity
DataCamp
5 Python Tutorial: Why use ML for marketing? Strategies and use cases
Python Tutorial: Why use ML for marketing? Strategies and use cases
DataCamp
6 Python Tutorial: Preparation for modeling
Python Tutorial: Preparation for modeling
DataCamp
7 Python Tutorial: Machine Learning modeling steps
Python Tutorial: Machine Learning modeling steps
DataCamp
8 R Tutorial: The prior model
R Tutorial: The prior model
DataCamp
9 R Tutorial: Data & the likelihood
R Tutorial: Data & the likelihood
DataCamp
10 R Tutorial: The posterior model
R Tutorial: The posterior model
DataCamp
11 R Tutorial: An Introduction to plotly
R Tutorial: An Introduction to plotly
DataCamp
12 R Tutorial: Plotting a single variable
R Tutorial: Plotting a single variable
DataCamp
13 R Tutorial: Bivariate graphics
R Tutorial: Bivariate graphics
DataCamp
14 Python Tutorial: Customer Segmentation in Python
Python Tutorial: Customer Segmentation in Python
DataCamp
15 Python Tutorial: Time cohorts
Python Tutorial: Time cohorts
DataCamp
16 Python Tutorial: Calculate cohort metrics
Python Tutorial: Calculate cohort metrics
DataCamp
17 Python Tutorial: Cohort analysis visualization
Python Tutorial: Cohort analysis visualization
DataCamp
18 R Tutorial: Building Dashboards with flexdashboard
R Tutorial: Building Dashboards with flexdashboard
DataCamp
19 R Tutorial: Anatomy of a flexdashboard
R Tutorial: Anatomy of a flexdashboard
DataCamp
20 R Tutorial: Layout basics
R Tutorial: Layout basics
DataCamp
21 R Tutorial: Advanced layouts
R Tutorial: Advanced layouts
DataCamp
22 Python Tutorial: Time Series Analysis in Python
Python Tutorial: Time Series Analysis in Python
DataCamp
23 Python Tutorial: Correlation of Two Time Series
Python Tutorial: Correlation of Two Time Series
DataCamp
24 Python Tutorial: Simple Linear Regressions
Python Tutorial: Simple Linear Regressions
DataCamp
25 Python Tutorial: Autocorrelation
Python Tutorial: Autocorrelation
DataCamp
26 R Tutorial: The gapminder dataset
R Tutorial: The gapminder dataset
DataCamp
27 R Tutorial: The filter verb
R Tutorial: The filter verb
DataCamp
28 R Tutorial: The arrange verb
R Tutorial: The arrange verb
DataCamp
29 R Tutorial: The mutate verb
R Tutorial: The mutate verb
DataCamp
30 R Tutorial: What is cluster analysis?
R Tutorial: What is cluster analysis?
DataCamp
31 R Tutorial: Distance between two observations
R Tutorial: Distance between two observations
DataCamp
32 R Tutorial: The importance of scale
R Tutorial: The importance of scale
DataCamp
33 R Tutorial: Measuring distance for categorical data
R Tutorial: Measuring distance for categorical data
DataCamp
34 Python Tutorial: Plotting multiple graphs
Python Tutorial: Plotting multiple graphs
DataCamp
35 Python Tutorial: Customizing axes
Python Tutorial: Customizing axes
DataCamp
36 Python Tutorial: Legends, annotations, & styles
Python Tutorial: Legends, annotations, & styles
DataCamp
37 Python Tutorial: Introduction to iterators
Python Tutorial: Introduction to iterators
DataCamp
38 Python Tutorial: Playing with iterators
Python Tutorial: Playing with iterators
DataCamp
39 Python Tutorial: Using iterators to load large files into memory
Python Tutorial: Using iterators to load large files into memory
DataCamp
40 SQL Tutorial: Introduction to Relational Databases in SQL
SQL Tutorial: Introduction to Relational Databases in SQL
DataCamp
41 SQL Tutorial: Tables: At the core of every database
SQL Tutorial: Tables: At the core of every database
DataCamp
42 SQL Tutorial: Update your database as the structure changes
SQL Tutorial: Update your database as the structure changes
DataCamp
43 Python Tutorial: Classification-Tree Learning
Python Tutorial: Classification-Tree Learning
DataCamp
44 Python Tutorial: Decision-Tree for Classification
Python Tutorial: Decision-Tree for Classification
DataCamp
45 Python Tutorial: Decision-Tree for Regression
Python Tutorial: Decision-Tree for Regression
DataCamp
46 Python Tutorial: Census Subject Tables
Python Tutorial: Census Subject Tables
DataCamp
47 Python Tutorial: Census Geography
Python Tutorial: Census Geography
DataCamp
48 Python Tutorial: Using the Census API
Python Tutorial: Using the Census API
DataCamp
49 R Tutorial: A/B Testing in R
R Tutorial: A/B Testing in R
DataCamp
50 R Tutorial: Baseline Conversion Rates
R Tutorial: Baseline Conversion Rates
DataCamp
51 R Tutorial: Designing an Experiment - Power Analysis
R Tutorial: Designing an Experiment - Power Analysis
DataCamp
52 R Tutorial: Introduction to qualitative data
R Tutorial: Introduction to qualitative data
DataCamp
53 R Tutorial: Understanding your qualitative variables
R Tutorial: Understanding your qualitative variables
DataCamp
54 R Tutorial: Making Better Plots
R Tutorial: Making Better Plots
DataCamp
55 SQL Tutorial: OLTP and OLAP
SQL Tutorial: OLTP and OLAP
DataCamp
56 SQL Tutorial: Storing data
SQL Tutorial: Storing data
DataCamp
57 SQL Tutorial: Database design
SQL Tutorial: Database design
DataCamp
58 Python Tutorial: Introduction to spaCy
Python Tutorial: Introduction to spaCy
DataCamp
59 Python Tutorial: Statistical Models
Python Tutorial: Statistical Models
DataCamp
60 Python Tutorial: Rule-based Matching
Python Tutorial: Rule-based Matching
DataCamp

Related AI Lessons

Up next
Business Combinations and Acquisition Accounting
Coursera
Watch →