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I want to make for loop formation with dataframe but i couldn't find grammar rule with this situation. Below is an overview of the functions I want to implement.
With Detail, i want to make new column named [df] which is calculated with column[f_adj]'s value.
Image of Excel
How to I fix this code?
df1['df'] = 0
for i in range(1,len(df1)-1):
df1['df'[i]] = df1['f_adj'[i+1]] - df1['f_adj'[i-1]]
Thank you in Advance
You should used iloc or loc in your code.
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import pandas as pd
Data = pd.open_csv('file name')
Data = isnull().sum()
I know that here we are testing each cell if it were empty or not; then, return the summation of empty ones.
Is there any other ways to re-write the statement?
Can we store the True results in a data structure, add them using a loop, and return the result?
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I have the below table in excel
and want to transpose like this
I trying with excel but now doing manually pls help mi with the quick solution
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I have one data frame in python. How can I calculate the 3sigma value for each column of my data frame using python? please help me with this.
The command you're looking for is df.std() * 3
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For the above example,
I want to have a look at the value of outlet_size when Outlet_identifier = OUT049 or any value for that instance.
I don't want to produce a new dataframe object and then print it, instead I want to know if there is any function or way to directly view it.
For both columns
df.loc[df['Outlet_identifier'].eq('OUT049'), ['Outlet_identifier', 'outlet_size']]
you can do that with pandas like this :
df = pd.DataFrame({'Outlet_identifier': ['OUT049','OUT018','OUT049'], 'outlet_size':
[2.0, 2.0, 2.0]})
df[df["Outlet_identifier"]=="OUT049"]["outlet_size"]
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Im trying to find a way to compare what students performed consistantly in their InternalAssessment_Performance to their FinalExam_Performance. Essentially i need to find what students have the same answer in both those columns.
How is it possible to compare the values in both commons and have them returned if they are the same?
Any help no matter how small would be great.
If the columns are aligned you can do something like this:
df[df['InternalAssessment_Performance'] == df['FinalExam_Performance']]