1What is one way to remove nulls in a dataset What is one way to remove nulls in a dataset using Pandas?
Use the drop.na() function to remove rows with null values. What type of data can ‘Int64’ handle?
2What function is used to replace NULL values in a dataset?
fillna()
3How do you replace all NULL values in a dataset with a specific value?
Use fillna() with a value, like 130.
4What is another method to replace NULL values using calculated statistics?
Replace NULLs with the mean, median, or mode.
5Which method calculates the mean for a specified column in Pandas?
mean()
6What is the mean value used to replace NULLs in the "Calories" column?
304.68
7How do you calculate the median value for a column in Pandas?
median()
8What was the median value calculated for the "Calories" column?
291.2
9What is the formula to calculate the median using rows 16 and 17?
(282.4 + 300) / 2 = 291.2
10How is the mode defined in terms of replacing NULL values?
Mode is the value that appears most frequently.
11What was the mode value used to replace NULLs in the "Calories" column?
300
12What is the function used to convert dates into the correct format in Pandas?
to_datetime()
13What happens when a NULL date value is encountered during cleaning?
It is stamped with NaT (Not a Time).
14How do you remove rows with NULL values in the "Date" column?
Use the dropna() method.
15What is the name of the book referenced in the lecture?
Data Science from Scratch by Joel Grus
16Where can you find additional resources on cleaning data with Pandas?
W3schools.com
17What is wrong data?
Data that is not null, not in the wrong date format, and just incorrect.
18What are some potential causes of wrong data?
Typo errors, deliberate attempts, miscalculations, wrong measurements, wrong formulas, inconsistencies in units of measurement, bugs, corrupted data, or incomplete data.
19How can you identify wrong data?
By analyzing the general format of columns, using intuition, applying industry knowledge, and consulting domain experts.
20What is an example of wrong data from the gym dataset?
A duration of 450 minutes when typical workout times are between 30 and 60 minutes.
21How can you fix wrong data in small datasets?
Replace the wrong data with the correct value manually.
22What is an option for fixing wrong data in large datasets?
Set rules as boundaries, and replace values that fall outside those boundaries.
23Why is removing rows with wrong data not recommended in data analysis?
Because removing rows may lead to loss of valuable information.
24How can you handle wrong data in the "Maxpulse" column?
If the value is less than 120, set it to 120, or remove rows with values higher than 120.
25What were some cleaning methods applied to the original dirty dataset?
Correct the date format, insert correct values, remove nulls, or insert the mean/median.
26What was the outcome of cleaning the dataset?
The clean dataset had 29 rows, with no nulls and correct data types.
27What was not fixed in the clean dataset?
Duplicates in rows 11 and 12 were not fixed.