Why is my program iterating through the row indexes and row elements instead of just row indexes when I use...












0














everyone! I am new to data science and I was playing around with pandas module in python. I wrote a code using for loop which is given below:
enter image description here



I then wrote the following code:



import numpy as np
for row in read.['OWN_OCCUPIED']:
read.loc[row,'OWN_OCCUPIED']=np.nan
print(read)



which shows the following the result:
enter image description here
I am really confused because why did the computer iterate through the row indexes and also the row elements i. e 'Y', 'N' and '12' ? Shouldn't it have iterated only eight times same as the row numbers?



But when I write this following code:



'import numpy as np
count = 0
for row in read['OWN_OCCUPIED']:
read.loc[count,'OWN_OCCUPIED']=np.nan
count += 1'


I get the desired result which is:
enter image description here
Why is this happening and can someone tell me the logic behind it?
Thank you.









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    everyone! I am new to data science and I was playing around with pandas module in python. I wrote a code using for loop which is given below:
    enter image description here



    I then wrote the following code:



    import numpy as np
    for row in read.['OWN_OCCUPIED']:
    read.loc[row,'OWN_OCCUPIED']=np.nan
    print(read)



    which shows the following the result:
    enter image description here
    I am really confused because why did the computer iterate through the row indexes and also the row elements i. e 'Y', 'N' and '12' ? Shouldn't it have iterated only eight times same as the row numbers?



    But when I write this following code:



    'import numpy as np
    count = 0
    for row in read['OWN_OCCUPIED']:
    read.loc[count,'OWN_OCCUPIED']=np.nan
    count += 1'


    I get the desired result which is:
    enter image description here
    Why is this happening and can someone tell me the logic behind it?
    Thank you.









    share







    New contributor




    user189206 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
    Check out our Code of Conduct.























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      0







      everyone! I am new to data science and I was playing around with pandas module in python. I wrote a code using for loop which is given below:
      enter image description here



      I then wrote the following code:



      import numpy as np
      for row in read.['OWN_OCCUPIED']:
      read.loc[row,'OWN_OCCUPIED']=np.nan
      print(read)



      which shows the following the result:
      enter image description here
      I am really confused because why did the computer iterate through the row indexes and also the row elements i. e 'Y', 'N' and '12' ? Shouldn't it have iterated only eight times same as the row numbers?



      But when I write this following code:



      'import numpy as np
      count = 0
      for row in read['OWN_OCCUPIED']:
      read.loc[count,'OWN_OCCUPIED']=np.nan
      count += 1'


      I get the desired result which is:
      enter image description here
      Why is this happening and can someone tell me the logic behind it?
      Thank you.









      share







      New contributor




      user189206 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.











      everyone! I am new to data science and I was playing around with pandas module in python. I wrote a code using for loop which is given below:
      enter image description here



      I then wrote the following code:



      import numpy as np
      for row in read.['OWN_OCCUPIED']:
      read.loc[row,'OWN_OCCUPIED']=np.nan
      print(read)



      which shows the following the result:
      enter image description here
      I am really confused because why did the computer iterate through the row indexes and also the row elements i. e 'Y', 'N' and '12' ? Shouldn't it have iterated only eight times same as the row numbers?



      But when I write this following code:



      'import numpy as np
      count = 0
      for row in read['OWN_OCCUPIED']:
      read.loc[count,'OWN_OCCUPIED']=np.nan
      count += 1'


      I get the desired result which is:
      enter image description here
      Why is this happening and can someone tell me the logic behind it?
      Thank you.







      python pandas





      share







      New contributor




      user189206 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.










      share







      New contributor




      user189206 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.








      share



      share






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