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',

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

4. Non-null count is the total number of blank data entries within a data column.

  • True
  • False

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()

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