iterate rows and print based on condition pandas python

Question

i have a dataset that i read in with pd.read_excel

Block     Con     
  1       100      
  1       100      
  1       100      
  1       33      
  1       33       
  1       33
  2       100
  2       100
  2       100
  2       33
  2       33
  2       33
...

there are a total of 10 'block's, each 'block' has 2 types of 'con': 100 and 33. how can i iterate through the 'Block' column so that for each 'block' it prints out the 2 types of 'con': 100 and 33

desire output:

      1      100
              33
      2       100
              33

my code:

for b in data.Block:
     for c in data.Con:
         print(c)

but it prints out all of the con for each row of block.

Andy Hayden · Accepted Answer · 2015-11-06 16:58:48Z

2

Use drop_duplicates:

In [11]: df
Out[11]:
    Block  Con
0       1  100
1       1  100
2       1  100
3       1   33
4       1   33
5       1   33
6       2  100
7       2  100
8       2  100
9       2   33
10      2   33
11      2   33

In [12]: df.drop_duplicates()
Out[12]:
   Block  Con
0      1  100
3      1   33
6      2  100
9      2   33

answered Nov 6, 2015 at 16:58

Andy Hayden

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3 Comments

Jessica Over a year ago

thank you, that makes perfect sense. but my actual table is much more complicated than this, that why i was wondering how to iterate through the rows by some condition. please see my edited post.

Andy Hayden Over a year ago

@Jessica you should ask this as another question rather than edit the old one to change it. That way if someone else googles for your question/answer they find this :)

Jessica Over a year ago

please see my new post here: stackoverflow.com/questions/33573329/…

Fabio Lamanna · Accepted Answer · 2015-11-06 16:59:29Z

0

I would use groupby in this way:

d = df.groupby(['Block','Con']).size()

which returns:

Block  Con
1      33     3
       100    3
2      33     3
       100    3

answered Nov 6, 2015 at 16:59

Fabio Lamanna

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2 Comments

Jessica Over a year ago

thank you, but my actual table is much more complicated than this, please see my edited post.

Jessica Over a year ago

please see my new post here: stackoverflow.com/questions/33573329/…

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