Consider the relation race. Which rows of data will be displayed by race.tail()? (1 point) Responses last five rows of the table last five rows of the table first five rows of the table first five rows of the table first three rows of the table first three rows of the table last three rows of the table
The correct answer is "last five rows of the table".
What are two of the functions of pandas and what do they mean?(1 point) Responses combining multiple datasets, sending data analysis to team
Two functions of pandas are:
1. Combining multiple datasets: Pandas provides functionalities to combine and merge multiple datasets based on common columns or indices. This allows for efficient data aggregation and analysis by consolidating data from multiple sources.
2. Sending data analysis to teams: Pandas provides capabilities for generating and sharing data analysis results with teams. It allows for easy creation and sharing of reports, visualizations, and insights derived from the data. This helps in collaboration and communication among team members working on data analysis tasks.
What are two of the functions of pandas and what do they mean?(1 point) Responses combining multiple datasets, sending data analysis to team members combining multiple datasets, sending data analysis to team members collecting data, cleaning data collecting data, cleaning data querying your dataset, grouping and aggregating your data querying your dataset, grouping and aggregating your data calculating measures of central tendency, calculating trigonometric problems
Two functions of pandas are:
1. Combining multiple datasets: Pandas provides functions to combine and merge multiple datasets based on common columns or indices. This allows for efficient data aggregation and analysis by consolidating data from different sources into a single dataset.
2. Querying your dataset, grouping, and aggregating your data: Pandas allows you to filter and query your dataset using various conditions, such as selecting rows based on specific criteria. It also enables you to group your data based on certain columns and perform aggregation operations like sum, mean, count, etc. on those groups. This helps in extracting meaningful insights and summaries from the data.
If you cannot view all your data because it contains too many columns, what code should you use?(1 point) Responses data.set_option("display.max.columns", None) data.set_option("display.max.columns", None) data.set_option("display.max.columns", Infinity) data.set_option("display.max.columns", Infinity) data.display.max.columns(True) data.display.max.columns(True) data.display.max.columns()
The correct code to use is:
```python
data.set_option("display.max.columns", None)
```
user = { 'name': 'Bruce', 'Address' : 'Gotham', 'subscription' : { 'title' : 'Student Bundle', 'cost' : 1000 } } print(user.get('subscription').get('title')) What will be the output of the code?
The output of the code will be:
```
Student Bundle
```