Revisions to How can I iterate over rows in a Pandas DataFrame?

Active reading [<https://en.wikipedia.org/wiki/Sentence_clause_structure#Run-on_sentences> <https://www.youtube.com/watch?v=1Dax90QyXgI&t=17m54s> <https://english.stackexchange.com/questions/4645/is-it-ever-correct-to-have-a-space-before-a-question-or-exclamation-mark#comment206109_4645>].

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edited Sep 4, 2022 at 23:06

Peter Mortensen

31.2k
22
111
134

We have multiple options to do the same, and lots of folks have shared their answers.

I found the below two methods easy and efficient to do :

Example:

 import pandas as pd
 inp = [{'c1':10, 'c2':100}, {'c1':11,'c2':110}, {'c1':12,'c2':120}]
 df = pd.DataFrame(inp)
 print (df)

 #With# With the iterrows method 

 for index, row in df.iterrows():
     print(row["c1"], row["c2"])

 #With# With the itertuples method

 for row in df.itertuples(index=True, name='Pandas'):
     print(row.c1, row.c2)

Note: itertuples() is supposed to be faster than iterrows()

We have multiple options to do the same, lots of folks have shared their answers.

I found below two methods easy and efficient to do :

Example:

 import pandas as pd
 inp = [{'c1':10, 'c2':100}, {'c1':11,'c2':110}, {'c1':12,'c2':120}]
 df = pd.DataFrame(inp)
 print (df)

 #With iterrows method 

 for index, row in df.iterrows():
     print(row["c1"], row["c2"])

 #With itertuples method

 for row in df.itertuples(index=True, name='Pandas'):
     print(row.c1, row.c2)

Note: itertuples() is supposed to be faster than iterrows()

We have multiple options to do the same, and lots of folks have shared their answers.

I found the below two methods easy and efficient to do:

Example:

 import pandas as pd
 inp = [{'c1':10, 'c2':100}, {'c1':11,'c2':110}, {'c1':12,'c2':120}]
 df = pd.DataFrame(inp)
 print (df)

 # With the iterrows method

 for index, row in df.iterrows():
     print(row["c1"], row["c2"])

 # With the itertuples method

 for row in df.itertuples(index=True, name='Pandas'):
     print(row.c1, row.c2)

Note: itertuples() is supposed to be faster than iterrows()

Rollback to Revision 1

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edited Jan 6, 2022 at 9:46

Sachin

1.7k
21
26

We have multiple options to do the same, and lots of folks have shared their answers.

I found below two methods easy and efficient to do :

Example:

 import pandas as pd
 inp = [{'c1':10, 'c2':100}, {'c1':11,'c2':110}, {'c1':12,'c2':120}]
 df = pd.DataFrame(inp)
 print (df)

 # With the#With iterrows method 

 for index, row in df.iterrows():
     print(row["c1"], row["c2"])

 # With the#With itertuples method

 for row in df.itertuples(index=True, name='Pandas'):
     print(row.c1, row.c2)

Note: itertuples() is supposed to be faster than iterrows()

We have multiple options to do the same, and lots of folks have shared their answers.

I found below two methods easy and efficient to do:

Example:

 import pandas as pd
 inp = [{'c1':10, 'c2':100}, {'c1':11,'c2':110}, {'c1':12,'c2':120}]
 df = pd.DataFrame(inp)
 print (df)

 # With the iterrows method

 for index, row in df.iterrows():
     print(row["c1"], row["c2"])

 # With the itertuples method

 for row in df.itertuples(index=True, name='Pandas'):
     print(row.c1, row.c2)

Note: itertuples() is supposed to be faster than iterrows()

We have multiple options to do the same, lots of folks have shared their answers.

I found below two methods easy and efficient to do :

Example:

 import pandas as pd
 inp = [{'c1':10, 'c2':100}, {'c1':11,'c2':110}, {'c1':12,'c2':120}]
 df = pd.DataFrame(inp)
 print (df)

 #With iterrows method 

 for index, row in df.iterrows():
     print(row["c1"], row["c2"])

 #With itertuples method

 for row in df.itertuples(index=True, name='Pandas'):
     print(row.c1, row.c2)

Note: itertuples() is supposed to be faster than iterrows()

Active reading [<english.stackexchange.com/questions/4645/is-it-ever-correct-to-have-a-space-before-a-question-or-exclamation-mark#comment206109_4645> <en.wikipedia.org/wiki/Sentence_clause_structure#Run-on_sentences> (see also <twitter.com/PeterMortensen/status/1199839973215739907>)].

Source Link

edited Jan 5, 2022 at 20:24

Peter Mortensen

31.2k
22
111
134

We have multiple options to do the same, and lots of folks have shared their answers.

I found below two methods easy and efficient to do :

Example:

 import pandas as pd
 inp = [{'c1':10, 'c2':100}, {'c1':11,'c2':110}, {'c1':12,'c2':120}]
 df = pd.DataFrame(inp)
 print (df)

 #With# With the iterrows method 

 for index, row in df.iterrows():
     print(row["c1"], row["c2"])

 #With# With the itertuples method

 for row in df.itertuples(index=True, name='Pandas'):
     print(row.c1, row.c2)

Note: itertuples() is supposed to be faster than iterrows()

We have multiple options to do the same, lots of folks have shared their answers.

I found below two methods easy and efficient to do :

Example:

 import pandas as pd
 inp = [{'c1':10, 'c2':100}, {'c1':11,'c2':110}, {'c1':12,'c2':120}]
 df = pd.DataFrame(inp)
 print (df)

 #With iterrows method 

 for index, row in df.iterrows():
     print(row["c1"], row["c2"])

 #With itertuples method

 for row in df.itertuples(index=True, name='Pandas'):
     print(row.c1, row.c2)

Note: itertuples() is supposed to be faster than iterrows()

We have multiple options to do the same, and lots of folks have shared their answers.

I found below two methods easy and efficient to do:

Example:

 import pandas as pd
 inp = [{'c1':10, 'c2':100}, {'c1':11,'c2':110}, {'c1':12,'c2':120}]
 df = pd.DataFrame(inp)
 print (df)

 # With the iterrows method

 for index, row in df.iterrows():
     print(row["c1"], row["c2"])

 # With the itertuples method

 for row in df.itertuples(index=True, name='Pandas'):
     print(row.c1, row.c2)

Note: itertuples() is supposed to be faster than iterrows()

Source Link

answered Nov 24, 2021 at 12:39

Sachin

1.7k
21
26

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