DATACAMP- Data Manipulation with Pandas|
EXAM PRACTICE QUESTIONS AND CORRECT
ANSWERS (100% CORRECT VERIFIED ANSWERS)
2024/2025
What is the difference between sorting and subsetting? - ✔✔While sorting organizes
the values by ascending e descending, subsetting just retrieve (or query) the data
passed in the arguments. In other words, it filters the DataFrame.
How and when to use the .isin() method? - ✔✔The best time to use .isin() is when
there is a need to subset multiple values of a categorical variable.
How to create/insert/mutate/transform/feature engineer a New Column in a
DataFrame? - ✔✔Just equate the new values on the right side and the new column
name on the left side.
What are summary statistics? And how it is used in Python? - ✔✔Summary statistics
are numbers that summarize and tells you about your dataset. Another definition is that
summary statistics summarizes a set of observations.
Summary statistics are calculated in Python via a series of methods, such as .sum(),
.mean(), etc...
What is the agg() function? - ✔✔The agg() function allows the possibility to compute
custom summary statistics.
How to use multiple summary statistics methods? - ✔✔It is possible to use multiple
summary statistics methods through the use of the agg() function.
, What is cumulative statistics? - ✔✔Cumulative statistics are calculations that
cumulate the value of the columns.
What is an important practice to do before counting (for Data Manipulation with
pandas)? - ✔✔Before summarizing categorical data, it is important to assure that
there is no double counting. To do so, there are some methods, as the .drop_values().
How counting functions are used in Data Manipulation with pandas? - ✔✔They are
important to count how many elements there are in a column.
What are Grouped Summary Statistics? - ✔✔While calculating the Summary Statistics
of all rows, it is also useful to group and compare different individuals groups. To do so,
we use Grouped Summary Statistics.
While calculating the Summary Statistics of all rows, it is also useful to group and
compare different individuals groups. To do so, we use Grouped Summary Statistics. -
✔✔Pivot Tables are tables of grouped values that aggregates the individual items of a
more extensive table within one or more discrete categories.
In other words, it is another way to calculate Grouped Summary Statistics.
What are indexes? - ✔✔Indexes are the position of values in a list or the first value in
a row of a DataFrame.
What is setting an index? Why is it important? - ✔✔Setting an index is to move a
column from the body of the DataFrame to the index. This is important to manipulate
DataFrames.
Why use Indexes? - ✔✔To make subsetting easier.
EXAM PRACTICE QUESTIONS AND CORRECT
ANSWERS (100% CORRECT VERIFIED ANSWERS)
2024/2025
What is the difference between sorting and subsetting? - ✔✔While sorting organizes
the values by ascending e descending, subsetting just retrieve (or query) the data
passed in the arguments. In other words, it filters the DataFrame.
How and when to use the .isin() method? - ✔✔The best time to use .isin() is when
there is a need to subset multiple values of a categorical variable.
How to create/insert/mutate/transform/feature engineer a New Column in a
DataFrame? - ✔✔Just equate the new values on the right side and the new column
name on the left side.
What are summary statistics? And how it is used in Python? - ✔✔Summary statistics
are numbers that summarize and tells you about your dataset. Another definition is that
summary statistics summarizes a set of observations.
Summary statistics are calculated in Python via a series of methods, such as .sum(),
.mean(), etc...
What is the agg() function? - ✔✔The agg() function allows the possibility to compute
custom summary statistics.
How to use multiple summary statistics methods? - ✔✔It is possible to use multiple
summary statistics methods through the use of the agg() function.
, What is cumulative statistics? - ✔✔Cumulative statistics are calculations that
cumulate the value of the columns.
What is an important practice to do before counting (for Data Manipulation with
pandas)? - ✔✔Before summarizing categorical data, it is important to assure that
there is no double counting. To do so, there are some methods, as the .drop_values().
How counting functions are used in Data Manipulation with pandas? - ✔✔They are
important to count how many elements there are in a column.
What are Grouped Summary Statistics? - ✔✔While calculating the Summary Statistics
of all rows, it is also useful to group and compare different individuals groups. To do so,
we use Grouped Summary Statistics.
While calculating the Summary Statistics of all rows, it is also useful to group and
compare different individuals groups. To do so, we use Grouped Summary Statistics. -
✔✔Pivot Tables are tables of grouped values that aggregates the individual items of a
more extensive table within one or more discrete categories.
In other words, it is another way to calculate Grouped Summary Statistics.
What are indexes? - ✔✔Indexes are the position of values in a list or the first value in
a row of a DataFrame.
What is setting an index? Why is it important? - ✔✔Setting an index is to move a
column from the body of the DataFrame to the index. This is important to manipulate
DataFrames.
Why use Indexes? - ✔✔To make subsetting easier.
