Pandas Series

Question 1

Where
my_list = [10,20,30]
:

pd.Series(data=my_list)

Answer 1

0 10
1 20
2 30
dtype: int64

Question 2

Where
labels = [‘a’,’b’,’c’]
my_list = [10,20,30]
:

pd.Series(data=my_list,index=labels)

Answer 2

a 10
b 20
c 30
dtype: int64

Question 3

Simplify pd.Series(data=my_list,index=labels)

Answer 3

pd.Series(my_list,labels)

Question 4

Where
arr = np.array([10,20,30])
:

pd.Series(arr)

Answer 4

0 10
1 20
2 30
dtype: int64

Question 5

Where
arr = np.array([10,20,30])
labels = [‘a’,’b’,’c’]
:

pd.Series(arr,labels)

Answer 5

a 10
b 20
c 30
dtype: int64

Question 6

Where
d = {‘a’:10,’b’:20,’c’:30}
:

pd.Series(d)

Answer 6

a 10
b 20
c 30
dtype: int64

Question 7

Where
labels = [‘a’,’b’,’c’]
:

pd.Series(data=labels)

Answer 7

0 a
1 b
2 c
dtype: object

Question 8

pd.Series([sum,print,len])

Answer 8

0 <built-in>
1 <built-in>
2 <built-in>
dtype: object</built-in></built-in></built-in>

Question 9

Where
ser1 = pd.Series([1,2,3,4],index = [‘USA’, ‘Germany’,’USSR’, ‘Japan’])
:

ser1

Answer 9

USA 1
Germany 2
USSR 3
Japan 4
dtype: int64

Question 10

Where
ser2 = pd.Series([1,2,5,4],index = [‘USA’, ‘Germany’,’Italy’, ‘Japan’])
:

ser2

Answer 10

USA 1
Germany 2
Italy 5
Japan 4
dtype: int64

Question 11

Where
ser1 = pd.Series([1,2,3,4],index = [‘USA’, ‘Germany’,’USSR’, ‘Japan’])
:

ser1[‘USA’]

Answer 11

1

Question 12

Where
ser1 = pd.Series([1,2,3,4],index = [‘USA’, ‘Germany’,’USSR’, ‘Japan’])

ser1[‘USA’]Where ser2 = pd.Series([1,2,5,4],index = [‘USA’, ‘Germany’,’Italy’, ‘Japan’])
:

ser1 + ser2

Answer 12

Germany 4.0
Italy NaN
Japan 8.0
USA 2.0
USSR NaN
dtype: float64