The next 4 questions are based on the following programming situation with Pandas:

You want to create the following pandas DataFrame df:

	date	A	B
0	2021-01-01	22	5
1	2021-02-01	10	VALUE_HIDDEN
2	2021-03-01	113	5

from the following component DataFrames, df1 and df2:

df1:

	date	A
0	2021-01-01	22
1	2021-02-01	10
2	2021-03-01	113

df2:

	date	B
0	2021-01-01	5
1	2021-03-01	5

Other notes:

Note that the first row and column are indices and header, respectively.

Further, here we don't care about the order of rows and columns as the required information is present somewhere in df.

1. Select all that apply:

Which of the following pandas methods can be used to create the DataFrame from component DataFrames df1 and df2?

Group of answer choices

a. df1 + df2

b. df1.merge(df2, on="date")

c. df1.join(df2)

d. df1.merge(df2)

e. df1.join(df2, on="date")

f. pd.concat(df1, df2)

g. pd.concat([df1, df2])

2. The value for the highlighted cell VALUE_HIDDEN after creating df from df1 and df2 is:

a. 2

b. 0

c. ValueError

d. NaN

e. ""

3. Filling in the blanks as if you were writing real Python code. Your output is case-sensitive.

Suppose we want to sort the resulting DataFrame df by date, in descending order, and display it. Complete the following code:

df. (by = , = False) 

4. Regarding the parameters of the function in the previous question:

Blank 2 is ["Required", "Optional"]

Blank 3 is ["Required", "Optional"]