 Did anyone do DS with Python the Missing Numbers assignment | Sololearn: Learn to code for FREE!

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# Did anyone do DS with Python the Missing Numbers assignment

Did someone did 3rd challenge from DS with python course? Mine always causes error. Here’s my code: import numpy as np import pandas lst = [float(x) if x != 'nan' else np.NaN for x in input().split()] from numpy import nan lst.fillna(lst.mean(), inplace=True) print(lst.isnull().sum()) DM please to explain!

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lst is a list. I think it should be a pandas dataframe.

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...series....and suddenly it is so easy. Thank you, Lisa! import numpy as np import pandas as pd lst = [float(x) if x != 'nan' else np.NaN for x in input().split()] ser = pd.Series(lst) mean= round(ser.mean(),1) ser = ser.where(ser.notna(),mean) print(ser)

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I have the same problem. The codes calculates the values correct, but when I print it, the result is correct, but the output ist missing the "dtype: float64" part. Adding a print(df.dtypes) doesn't work either, because the output states dtype object....

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Trochoide What type does your result have?

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Lisa I cannot copy paste the result, nor can I Post a Screenshot (or can I?), so I am typing the output 0 3.0 .... .... .... 6 3.8 floating64 dtype: object code: df=pd.DataFrame(lst, columns=[""]) print(df) print(df.dtypes)

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Trochoide You should be able to copy your code. Then you could save it in playground and link it. I looked it up how I solved it: I converted lst to a pandas series, replaced the nan and only printed the series in the end (it was float64)

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import numpy as np import pandas as pd lst = [float(x) if x != 'nan' else np.NaN for x in input().split()] ser=pd.Series(lst) mean_val = round(ser.mean(),1) ser1=ser.fillna(value=mean_val) print(ser1)

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So looking at the replies above, Lisa and Apoorva Datir were able to solve the project by using a Series. When you print the Series, the output is in exactly the right format (with the data type at the end, for example). The project actually says that we should convert the data into a DataFrame. But when you print the DataFrame, the output is NOT in exactly the required format. This is what Bat-Ochir Artur was saying.