how to drow an exponontiel plot of this situation with python












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$begingroup$


I have a dataset with binary output (Y) and I have a column (Duration) contains the duration of each task stored by "days" and varied from 1day to 350days.



when I think logically in our situation, I can deduce that the probability of getting a positive output value (Y = 1) require to have small duration task.



But I need to justify my opinion with some plots



I have tried the following source code but It doesn't represent correctly my assumption. 



#LoadData



min_duration = plot_data['Duration'].min()

max_duration = plot_data['Duration'].max()

xr_ = list(range(min_duration,  max_duration,  5))

y_ = 



for i in range(0,(len(xr_)-1)):

    a_ = np.logical_and(plot_data['Duration'].values >= xr_[i], plot_data['Duration'].values < xr_[i+1])

    b_ = np.logical_and(np.logical_and(plot_data['Duration'].values >= xr_[i], plot_data['Duration'].values < xr_[i+1]), plot_data['output'].values==1)

    y_.append(sum(b_)/sum(a_))



import matplotlib

matplotlib.pyplot.plot(xr_[1:len(xr_)], y_, 'o')


Based on my previous assumption I must get a plot which contains an exponential form like :



enter image description here



But I have got contrary the following plot:



enter image description here



I want to know where I have a mistake and If there is any other method to justify my assumption






python dataset matplotlib






share









$endgroup$

















    0












    $begingroup$


    I have a dataset with binary output (Y) and I have a column (Duration) contains the duration of each task stored by "days" and varied from 1day to 350days.



    when I think logically in our situation, I can deduce that the probability of getting a positive output value (Y = 1) require to have small duration task.



    But I need to justify my opinion with some plots



    I have tried the following source code but It doesn't represent correctly my assumption. 



    #LoadData
    

    
min_duration = plot_data['Duration'].min()
    
max_duration = plot_data['Duration'].max()
    
xr_ = list(range(min_duration,  max_duration,  5))
    
y_ = 
    

    
for i in range(0,(len(xr_)-1)):
    
    a_ = np.logical_and(plot_data['Duration'].values >= xr_[i], plot_data['Duration'].values < xr_[i+1])
    
    b_ = np.logical_and(np.logical_and(plot_data['Duration'].values >= xr_[i], plot_data['Duration'].values < xr_[i+1]), plot_data['output'].values==1)
    
    y_.append(sum(b_)/sum(a_))
    

    
import matplotlib
    
matplotlib.pyplot.plot(xr_[1:len(xr_)], y_, 'o')


    Based on my previous assumption I must get a plot which contains an exponential form like :



    enter image description here



    But I have got contrary the following plot:



    enter image description here



    I want to know where I have a mistake and If there is any other method to justify my assumption






    python dataset matplotlib






    share









    $endgroup$















      0












      0








      0





      $begingroup$


      I have a dataset with binary output (Y) and I have a column (Duration) contains the duration of each task stored by "days" and varied from 1day to 350days.



      when I think logically in our situation, I can deduce that the probability of getting a positive output value (Y = 1) require to have small duration task.



      But I need to justify my opinion with some plots



      I have tried the following source code but It doesn't represent correctly my assumption. 



      #LoadData
      

      
min_duration = plot_data['Duration'].min()
      
max_duration = plot_data['Duration'].max()
      
xr_ = list(range(min_duration,  max_duration,  5))
      
y_ = 
      

      
for i in range(0,(len(xr_)-1)):
      
    a_ = np.logical_and(plot_data['Duration'].values >= xr_[i], plot_data['Duration'].values < xr_[i+1])
      
    b_ = np.logical_and(np.logical_and(plot_data['Duration'].values >= xr_[i], plot_data['Duration'].values < xr_[i+1]), plot_data['output'].values==1)
      
    y_.append(sum(b_)/sum(a_))
      

      
import matplotlib
      
matplotlib.pyplot.plot(xr_[1:len(xr_)], y_, 'o')


      Based on my previous assumption I must get a plot which contains an exponential form like :



      enter image description here



      But I have got contrary the following plot:



      enter image description here



      I want to know where I have a mistake and If there is any other method to justify my assumption






      python dataset matplotlib






      share









      $endgroup$




      I have a dataset with binary output (Y) and I have a column (Duration) contains the duration of each task stored by "days" and varied from 1day to 350days.



      when I think logically in our situation, I can deduce that the probability of getting a positive output value (Y = 1) require to have small duration task.



      But I need to justify my opinion with some plots



      I have tried the following source code but It doesn't represent correctly my assumption. 



      #LoadData
      

      
min_duration = plot_data['Duration'].min()
      
max_duration = plot_data['Duration'].max()
      
xr_ = list(range(min_duration,  max_duration,  5))
      
y_ = 
      

      
for i in range(0,(len(xr_)-1)):
      
    a_ = np.logical_and(plot_data['Duration'].values >= xr_[i], plot_data['Duration'].values < xr_[i+1])
      
    b_ = np.logical_and(np.logical_and(plot_data['Duration'].values >= xr_[i], plot_data['Duration'].values < xr_[i+1]), plot_data['output'].values==1)
      
    y_.append(sum(b_)/sum(a_))
      

      
import matplotlib
      
matplotlib.pyplot.plot(xr_[1:len(xr_)], y_, 'o')


      Based on my previous assumption I must get a plot which contains an exponential form like :



      enter image description here



      But I have got contrary the following plot:



      enter image description here



      I want to know where I have a mistake and If there is any other method to justify my assumption






      python dataset matplotlib




      python dataset matplotlib





      share












      share










      share



      share










      asked 7 mins ago









      NirmineNirmine

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