Screen Link:
https://app.dataquest.io/m/314/dictionaries-and-frequency-tables/12/frequency-tables-for-numerical-columns
My Code:
opened_file = open('AppleStore.csv')
from csv import reader
read_file = reader(opened_file)
apps_data = list(read_file)
data_sizes=[]
for i in apps_data[1:]:
size=float(i[2])
data_sizes.append(size)
# min_size=min(data_sizes)
# max_size=max(data_sizes)
for i in data_sizes:
base_value= data_sizes[0]
if i<base_value:
base_value=i
min_size=base_value
for i in data_sizes:
base_value_1= data_sizes[0]
if i>base_value_1:
base_value_1=i
max_size=base_value_1
print(min_size)
print(max_size)
What I expected to happen:
min_size = 589824.0
max_size = 4025969664.0
What actually happened:
51174400.0
389879808.0
I am just curious how is my code wrong, i’ll been on this for the past 30 mins, and i can’t understand why. Could someone aid me in finding the right answer?
You need to loop app_data[1:]
, then append size
, which is in the third column to data_sizes
.
This code is unnecessary
.
Comment out this code. 
This is how I solved.
opened_file = open('AppleStore.csv')
from csv import reader
read_file = reader(opened_file)
apps_data = list(read_file)
data_sizes = []
for app_data in apps_data[1:]:
size = float(app_data[2])
data_sizes.append(size)
min_size = min(data_sizes)
print(min_size)
max_size = max(data_sizes)
print(max_size)
1 Like
Thank you! What if i just wanted to use the method whereby i could - Assign first element as a minimum, and find the min and max from there on?
How can i do so? I wanted to know if i can find max and min using such a method.
Thank you!
If I understand you, you want to assign the minimum and maximum values to different variables right?
From what @info.victoromondi has explained, you can take it a step further by simply assigning a variable to the min and max values.
data_sizes = []
for app_data in apps_data[1:]:
size = float(app_data[2])
data_sizes.append(size)
min_size = min(data_sizes)
max_size = max(data_sizes)
base_value = min(data_sizes)
base_value_1 = max(data_sizes)