+ 2
Pandas pandas pandas project in Data Science course
My code is not working for test case 3. I tried to revise the code again and again but I donât know what is wrong here. Can anybody give me a clue where my code went wrong? Also does anybody know what is the test case 3? https://code.sololearn.com/c6w3kYK2HrOu/?ref=app
14 RĂ©ponses
+ 2
if n1 or n2 is null you will have an error on line 25 or line 26. I suggest you, before calculating the means to first test if those numbers are not null.
I suppose that in this test, one of your variables n1 or n2 will be null.
+ 2
you're welcome. keep practicing.
+ 1
Here is my solution:
https://www.sololearn.com/Discuss/2730223/
Could anyone help?
+ 1
Mir Abir Hossain how did you fix it? Can you show please?
+ 1
Mir Abir Hossain figured it out thanks.
+ 1
#THANKS John Robotane
n = int(input())
import numpy as np
def eudt(lista,listb):
lista,listb=np.array(lista), np.array(listb)
diff=lista-listb
return ((diff[0]**2)+(diff[1]**2))**0.5
w=np.zeros((n,2))
for i in range(n):
w[i,]=[float(j) for j in input().split()]
distances=np.zeros((n,2))
for i in range(n):
distances[i,]=[eudt(w[i,],[0,0]),eudt(w[i,],[2,2])]
team0=w[(distances[:,0]<=distances[:,1]),]
team2=w[(distances[:,0]>distances[:,1]),]
if sum(distances[:,0]<=distances[:,1])!=0:
zeromn=np.around(team0.mean(axis=0),2)
if sum(distances[:,0]>distances[:,1])!=0:
twoavg=np.around(team2.mean(axis=0),2)
if sum(distances[:,0]<=distances[:,1])==0:
zeromn=None
elif sum(distances[:,0]>distances[:,1])==0:
twoavg=None
else:
pass
print(zeromn)
print(twoavg)
0
John Robotane thanks a lot for the suggestion ^_^ Let me try
0
John Robotane it worked. Thanks <3
0
Zach Z I have fixed the code above. You can click and see it. Probably it is understandable. If not, then I will explain again.
0
Hey Mir Abir Hossain nvm i saw the issie but its still not solving #3?
0
Zach Z can you show me your code?
0
Zach Z welcome
0
import numpy as np
n = int(input())
points = []
for i in range(n):
x, y = input().split()
x, y = [float(i) for i in [x,y]]
points.extend([[x,y]])
a = np.array([0,0])
b = np.array([2,2])
grp1 = []
grp2 = []
for j in points:
d1 = np.linalg.norm(a-j)
d2 = np.linalg.norm(b-j)
if d1 > d2 :
grp2.extend(j)
else :
grp1.extend(j)
grp1 = np.array(grp1)
x= int(grp1.size/2)
grp1 = np.reshape(grp1,(x,2))
mask = grp1.mean(axis=0)
grp2 = np.array(grp2)
y= int(grp2.size/2)
grp2 = np.reshape(grp2,(y,2))
mask2 = grp2.mean(axis=0)
print(mask.round(2))
print(mask2.round(2))
hi every one I tried this but I got the same error, in case number 3, I don't know what to do ? if any one could help me pass it, I'll be happy.
- 2
Thank you Airat Halitovđ„