Module 3 Quiz - Data Science

Question

My problem is in the Quiz of module 3, from Data Science course. It could be said that I already have solved this problem, but at the end of my output there is something that I do not want, I mean, IDK how to quit that part; what I'm talking about is this:

Name: 0, dtype: float64

I would like to have just the 'dtype', so what could I do, my code is the following if you want to check and tell me if something I put is causing this:

import pandas as pd
import numpy as np

lst = [float(x) if x != 'nan' else 'NaN' for x in input().split()]

new_lst = []

for j in lst:
if j == 'NaN':
continue
else:
new_lst.append(j)

mean = np.mean(new_lst)

for i in lst:
if i == 'NaN':
index = lst.index(i)
lst.remove(i)
lst.insert(index, mean.round(1))
else:
continue

lst = pd.DataFrame(lst)

print(lst[0])

Answer 1

Think more about Pandas Series, because the output, it looks like a series, your output is a dataframe... something like this?

https://code.sololearn.com/cfag9BiW4MO5/?ref=app

Answer 2

Sometimes you don't need to drop the whole row especially when you are preparing your data for a classifier.. fillna() fills the position of NaN values with the given argument.

Answer 3

Oh that's fairly handy, thanks Ahmed Yasser :D

Answer 4

( •_•)>⌐■-■ Dude I forgot about series, you cannot be more right, thanks a lot you solve my problem :D

Answer 5

import numpy as np
r = int(input())
lst = [float(x) for x in input().split()]

arr_ABD = np.array(lst)
arr_ABD = arr_ABD.reshape(r,int(len(lst)/r))
print(arr_ABD.round(2))

Answer 6

Just a question, how does the function fillna() works?? I mean when I have to use it, I cannot entirely get it.

Answer 7

Copy this code answer and like and check thank-you

Answer 8

I'm doing the same exercise in Sololearn (#3, missing numbers) and it actually states in the task that you have to put the data in a pandas DataFrame. Then you have to make sure that the missing numbers (NaN) will become replaced by the mean of the rest of the numbers. I did all that with the following code, but now I am frustrated by the same problem as mentioned above... the last line contains "Name: 0, dtype: float64" and according to Sololearn that's not correct, it should just say" dtype: float 64" as last line. Any suggestions? This is the code I use:

mport numpy as np
import pandas as pd
lst=[float(x) if x!='nan' else np.NaN for x in input().split()]
for i in range(0,len(lst)):
if np.isnan(lst[i])==True:
lst[i]=round(np.nanmean(lst),1)
df=pd.DataFrame([lst])
print(df.loc[0,0:6])