The following is a preview of the DataFrames df_1. Which of the following statement(s) are true? df_1 date temperature humidity 2018/01/01 70 85 2018/01/02 68 80 2018/01/03 71 80 df_1 is in long format because each row represents an observation and each column represents a variable. df 1 is in wide format, i.e, each row is 1 record of an observation and each column represents a feature about a record. A dataframe cannot be seen as a table.
The following is a preview of the DataFrames df_1. Which of the following statement(s) are true? df_1 date temperature humidity 2018/01/01 70 85 2018/01/02 68 80 2018/01/03 71 80 df_1 is in long format because each row represents an observation and each column represents a variable. df 1 is in wide format, i.e, each row is 1 record of an observation and each column represents a feature about a record. A dataframe cannot be seen as a table.
Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
Section: Chapter Questions
Problem R1RQ: What is the difference between a host and an end system? List several different types of end...
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### DataFrame Understanding: Educational Example
The following is a preview of the DataFrame named `df_1`. Which of the following statement(s) are true?
#### df_1 Preview:
| date | temperature | humidity |
|------------|--------------|----------|
| 2018/01/01 | 70 | 85 |
| 2018/01/02 | 68 | 80 |
| 2018/01/03 | 71 | 80 |
#### Statements:
- [ ] **df_1 is in long format because each row represents an observation and each column represents a variable.**
- [x] **df_1 is in wide format, i.e., each row is 1 record of an observation and each column represents a feature about a record.**
- [ ] **A dataframe cannot be seen as a table.**
#### Explanation:
The table above showcases a DataFrame in wide format. Each row represents a unique record with specific observations, and each column corresponds to a different feature of those observations. This data format is particularly useful for scenarios where each record (row) needs to be individually identifiable, and feature-specific columns can make data analysis straightforward.
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Transcribed Image Text:---
### DataFrame Understanding: Educational Example
The following is a preview of the DataFrame named `df_1`. Which of the following statement(s) are true?
#### df_1 Preview:
| date | temperature | humidity |
|------------|--------------|----------|
| 2018/01/01 | 70 | 85 |
| 2018/01/02 | 68 | 80 |
| 2018/01/03 | 71 | 80 |
#### Statements:
- [ ] **df_1 is in long format because each row represents an observation and each column represents a variable.**
- [x] **df_1 is in wide format, i.e., each row is 1 record of an observation and each column represents a feature about a record.**
- [ ] **A dataframe cannot be seen as a table.**
#### Explanation:
The table above showcases a DataFrame in wide format. Each row represents a unique record with specific observations, and each column corresponds to a different feature of those observations. This data format is particularly useful for scenarios where each record (row) needs to be individually identifiable, and feature-specific columns can make data analysis straightforward.
---
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