go beyond the numbers: translate data into insights coursera weekly challenge 3 answers
Test your knowledge: The challenge of missing or duplicate data
1. Fill in the blank: Missing data has a value that is not stored for a _____ in a dataset.
- column
- row
- visualization
- variable
2. A data professional requests additional information from a dataset’s original owner. Unfortunately, they are not able to provide the information. Therefore, the data professional creates a NaN category in the dataset. What concept does this scenario describe?
- Ensuring two datasets are compatible
- Managing big data
- Mapping variables in a dataset
- Solving the problem of missing data
3. When merging data, a data professional uses the following code:
df_joined = df.merge(df_zip, how='left',
on=['date','center_point_geom'])
What is the function of the parameters how and on in this code?
- To tell Python how to find missing values in the rows and columns
- To tell Python which way to join the data and which column to join from
- To tell Python how to place the appropriate values on the top row of the dataset
- To tell Python which datasets should be merged
Test your knowledge: The ins and outs of data outliers
5. What type of outlier is a normal data point under certain conditions, but becomes an anomaly under most other conditions?
- Collective outlier
- Contextual outlier
- Global outlier
- Constant outlier
6. What is the term for a line of text that follows a method or function, which is used to explain the purpose of that method or function to others using the same code?
- Factor
- Annotation
- Argument
- Docstring
7. A data professional is using a box plot to identify suspected high outliers in a dataset, according to the interquartile rule. To do that, they search for data points greater than the third quartile plus what standard of the interquartile range?
- 1.5 times
- 3 times
- 10 times
- .5 times
Test your knowledge: Changing categorical data to numerical data
8. Fill in the blank: Label encoding assigns each category a unique _____ instead of a qualitative value.
- character
- qualifier
- string
- number
Shuffle Q/A 1
9. When working with dummy variables, data professionals may assign the variables an infinite number of values.
- True
- False
10. Which pandas function does a data professional use to convert categorical variables into dummy variables?
- get_dummies()
- convert_categories()
- convert_dummies()
- get_categories()
