Data Analysis with Python Week 2 Quiz Answer

Data Analysis with Python 

Week 2 Quiz Answer

Practice Quiz 1

Dealing with Missing Values in Python

Q1) How would you access the column "body-style" from the dataframe df?

• dff {"body-style"]

• df =="bodystyle"

Q2) How would you replace the missing values in the column "normalized-losses" with the mean of that column?

• mean = df ["normalized-losses"].mean() 
• df["normalized-losses").replace(np.nan, mean)

• df.dropna(subset=["price"], axis-8, inplace - True)

Q3) What is the correct symbol for missing data?

• nan

• no-data

Practice Quiz 2

Data Formatting in Python

Q1) How would you multiply each element in the column df["a"] by 2 and assign it back to the column df["a"?

• 2*df["a")

• df["a")=2*df{"a")

• df["a"]=df["a"]-1

Q2) How would you rename the column "city_mpg" to "city-L/100km"?

• df.rename(columns-{"city_mpg": "city-L/100km"), inplace-True)

• df.rename(columns-{"city_mpg": "city-L/100km"})

Practice Quiz 3

Data Normalization in Python

Q1) Which of the following is the correct formula for 2-score or data standardization?

•  C

Q2) Consider the column "length"; select the correct code for z-score or standard score.

• df["length"] = (df["length"]-df["length"].min()/
• (df["length"].max()-df["length"].min())

• df ["length"] = (df["length"]-df["length"].mean())/df["length"].std()

Practice Quiz 4

Data Wrangling

Q1) What task does the following line of code perform?

df['peak-rpn'].mean()

• calculate the mean of the column "peak-rpm
• calculate the mean of the dataframe df
• replace missing data with the mean value from the column 'peak-rpm'

Q2) What task do the following lines of code perform?

avg-df('bare').mean(axis-a) 

df['bore').replace(np.nan, avg, inplace=True)

• calculate the mean value for the "bore' column and replace all the NaN values of that column by the mean value
• nothing because the parameter inplace is not set to true
• horsepower

Q3) How would you rename column name from "highway.mpg" to "highway-L/100km"?

• df.rename(columns-{"highway - mpe"': 'highway-L/100km'}, inplace-True)

• rename(df,columns={""highway-mpg"': 'highway-L/100km'})

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Data Analysis with Python

• Data Analysis with Python Week 1 Quiz Answer

• Data Analysis with Python Week 2 Quiz Answer

• Data Analysis with Python Week 3 Quiz Answer

• Data Analysis with Python Week 4 Quiz Answer

• Data Analysis with Python Week 5 Quiz Answer

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