Looping through dictionaries

student_dict = {
	"student": ["Angela", "James", "Lily"],
	"score": [56, 76, 98]
}

#Looping through dictionaries:
for (key, value) in student_dict.items():
	print(key)
	print(value)

-------
student
score

["Angela", "James", "Lily"]
[56, 76, 98]

Loop through rows of a data frame

student_dict = {
	"student": ["Angela", "James", "Lily"],
	"score": [56, 76, 98]
}

import pandas

student_data_frame = pandas.DataFrame(student_dict)
print(student_data_frame)

#Loop through rows of a data frame
for (index, value) in student_data_frame.items():
	print(key)
	print(value)

---------
#print(student_data_frame)
student  score
0  Angela     56
1   James     76
2    Lily     98

#print(key)
student
score

#print(value)
student
0    Angela
1     James
2      Lily
Name: student, dtype: object
score
0    56
1    76
2    98
Name: score, dtype: int64

Iterrows() : Loop through rows of a data frame

student_dict = {
	"student": ["Angela", "James", "Lily"],
	"score": [56, 76, 98]
}

import pandas

student_data_frame = pandas.DataFrame(student_dict)
print(student_data_frame)

#Loop through rows of a data frame
for (index, row) in student_data_frame.iterrows():
	print(index)
	print(row)
	print(row.student)
	print(row.score)
	if row.student == "Angela":
		print(row.score)

---------

#print(index)
0
1
2

#print(row) 
0
student    Angela
score          56
Name: 0, dtype: object
1
student    James
score         76
Name: 1, dtype: object
2
student    Lily
score        98
Name: 2, dtype: object

#print(row.student)
Angela
James
Lily

#print(row.score)
56
76
98

• Each of the row is a panda series object ⇒ we can tap into the row and then get hold of the value under a particular column by using the dot notation.