V tem članku bomo obravnavali kako iterirati po vrsticah v DataFrame v Pandas .
Kako iterirati po vrsticah v DataFrame v Pandas
Python je odličen jezik za analizo podatkov, predvsem zaradi fantastičnega ekosistema paketov Python, osredotočenih na podatke. Pande je eden od teh paketov in omogoča veliko lažje uvažanje in analiziranje podatkov.
Oglejmo si različne načine ponavljanja vrstic v Pandas Dataframe :
1. način: uporaba atributa indeksa Dataframe.
Python3
zgoščevanje v strukturi podatkov
# import pandas package as pd> import> pandas as pd> # Define a dictionary containing students data> data>=> {>'Name'>: [>'Ankit'>,>'Amit'>,> >'Aishwarya'>,>'Priyanka'>],> >'Age'>: [>21>,>19>,>20>,>18>],> >'Stream'>: [>'Math'>,>'Commerce'>,> >'Arts'>,>'Biology'>],> >'Percentage'>: [>88>,>92>,>95>,>70>]}> # Convert the dictionary into DataFrame> df>=> pd.DataFrame(data, columns>=>[>'Name'>,>'Age'>,> >'Stream'>,>'Percentage'>])> print>(>'Given Dataframe :
'>, df)> print>(>'
Iterating over rows using index attribute :
'>)> # iterate through each row and select> # 'Name' and 'Stream' column respectively.> for> ind>in> df.index:> >print>(df[>'Name'>][ind], df[>'Stream'>][ind])> |
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Izhod:
Given Dataframe : Name Age Stream Percentage 0 Ankit 21 Math 88 1 Amit 19 Commerce 92 2 Aishwarya 20 Arts 95 3 Priyanka 18 Biology 70 Iterating over rows using index attribute : Ankit Math Amit Commerce Aishwarya Arts Priyanka Biology>
2. način: Uporaba mesto[] funkcijo Dataframe.
Python3
dvodimenzionalni matrični program v c
# import pandas package as pd> import> pandas as pd> # Define a dictionary containing students data> data>=> {>'Name'>: [>'Ankit'>,>'Amit'>,> >'Aishwarya'>,>'Priyanka'>],> >'Age'>: [>21>,>19>,>20>,>18>],> >'Stream'>: [>'Math'>,>'Commerce'>,> >'Arts'>,>'Biology'>],> >'Percentage'>: [>88>,>92>,>95>,>70>]}> # Convert the dictionary into DataFrame> df>=> pd.DataFrame(data, columns>=>[>'Name'>,>'Age'>,> >'Stream'>,> >'Percentage'>])> print>(>'Given Dataframe :
'>, df)> print>(>'
Iterating over rows using loc function :
'>)> # iterate through each row and select> # 'Name' and 'Age' column respectively.> for> i>in> range>(>len>(df)):> >print>(df.loc[i,>'Name'>], df.loc[i,>'Age'>])> |
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Izhod:
Given Dataframe : Name Age Stream Percentage 0 Ankit 21 Math 88 1 Amit 19 Commerce 92 2 Aishwarya 20 Arts 95 3 Priyanka 18 Biology 70 Iterating over rows using loc function : Ankit 21 Amit 19 Aishwarya 20 Priyanka 18>
3. način: Uporaba iloc[] funkcijo DataFrame.
Python3
# import pandas package as pd> import> pandas as pd> # Define a dictionary containing students data> data>=> {>'Name'>: [>'Ankit'>,>'Amit'>,> >'Aishwarya'>,>'Priyanka'>],> >'Age'>: [>21>,>19>,>20>,>18>],> >'Stream'>: [>'Math'>,>'Commerce'>,> >'Arts'>,>'Biology'>],> >'Percentage'>: [>88>,>92>,>95>,>70>]}> # Convert the dictionary into DataFrame> df>=> pd.DataFrame(data, columns>=>[>'Name'>,>'Age'>,> >'Stream'>,>'Percentage'>])> print>(>'Given Dataframe :
'>, df)> print>(>'
Iterating over rows using iloc function :
'>)> # iterate through each row and select> # 0th and 2nd index column respectively.> for> i>in> range>(>len>(df)):> >print>(df.iloc[i,>0>], df.iloc[i,>2>])> |
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Izhod:
Given Dataframe : Name Age Stream Percentage 0 Ankit 21 Math 88 1 Amit 19 Commerce 92 2 Aishwarya 20 Arts 95 3 Priyanka 18 Biology 70 Iterating over rows using iloc function : Ankit Math Amit Commerce Aishwarya Arts Priyanka Biology >
4. način: Uporaba iterrows() metoda Dataframe.
Python3
vodni žig v wordu
# import pandas package as pd> import> pandas as pd> # Define a dictionary containing students data> data>=> {>'Name'>: [>'Ankit'>,>'Amit'>,> >'Aishwarya'>,>'Priyanka'>],> >'Age'>: [>21>,>19>,>20>,>18>],> >'Stream'>: [>'Math'>,>'Commerce'>,> >'Arts'>,>'Biology'>],> >'Percentage'>: [>88>,>92>,>95>,>70>]}> # Convert the dictionary into DataFrame> df>=> pd.DataFrame(data, columns>=>[>'Name'>,>'Age'>,> >'Stream'>,>'Percentage'>])> print>(>'Given Dataframe :
'>, df)> print>(>'
Iterating over rows using iterrows() method :
'>)> # iterate through each row and select> # 'Name' and 'Age' column respectively.> for> index, row>in> df.iterrows():> >print>(row[>'Name'>], row[>'Age'>])> |
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Izhod:
Given Dataframe : Name Age Stream Percentage 0 Ankit 21 Math 88 1 Amit 19 Commerce 92 2 Aishwarya 20 Arts 95 3 Priyanka 18 Biology 70 Iterating over rows using iterrows() method : Ankit 21 Amit 19 Aishwarya 20 Priyanka 18>
5. način: Uporaba itertuples() metodo Dataframe.
Python3
# import pandas package as pd> import> pandas as pd> # Define a dictionary containing students data> data>=> {>'Name'>: [>'Ankit'>,>'Amit'>,>'Aishwarya'>,> >'Priyanka'>],> >'Age'>: [>21>,>19>,>20>,>18>],> >'Stream'>: [>'Math'>,>'Commerce'>,>'Arts'>,> >'Biology'>],> >'Percentage'>: [>88>,>92>,>95>,>70>]}> # Convert the dictionary into DataFrame> df>=> pd.DataFrame(data, columns>=>[>'Name'>,>'Age'>,> >'Stream'>,> >'Percentage'>])> print>(>'Given Dataframe :
'>, df)> print>(>'
Iterating over rows using itertuples() method :
'>)> # iterate through each row and select> # 'Name' and 'Percentage' column respectively.> for> row>in> df.itertuples(index>=>True>, name>=>'Pandas'>):> >print>(>getattr>(row,>'Name'>),>getattr>(row,>'Percentage'>))> |
java niz bajtov v niz
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Izhod:
Given Dataframe : Name Age Stream Percentage 0 Ankit 21 Math 88 1 Amit 19 Commerce 92 2 Aishwarya 20 Arts 95 3 Priyanka 18 Biology 70 Iterating over rows using itertuples() method : Ankit 88 Amit 92 Aishwarya 95 Priyanka 70 >
6. način: Uporaba uporabi() metoda Dataframe.
Python3
# import pandas package as pd> import> pandas as pd> # Define a dictionary containing students data> data>=> {>'Name'>: [>'Ankit'>,>'Amit'>,>'Aishwarya'>,> >'Priyanka'>],> >'Age'>: [>21>,>19>,>20>,>18>],> >'Stream'>: [>'Math'>,>'Commerce'>,>'Arts'>,> >'Biology'>],> >'Percentage'>: [>88>,>92>,>95>,>70>]}> # Convert the dictionary into DataFrame> df>=> pd.DataFrame(data, columns>=>[>'Name'>,>'Age'>,>'Stream'>,> >'Percentage'>])> print>(>'Given Dataframe :
'>, df)> print>(>'
Iterating over rows using apply function :
'>)> # iterate through each row and concatenate> # 'Name' and 'Percentage' column respectively.> print>(df.>apply>(>lambda> row: row[>'Name'>]>+> ' '> +> >str>(row[>'Percentage'>]), axis>=>1>))> |
niz v logično javo
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Izhod:
Given Dataframe : Name Age Stream Percentage 0 Ankit 21 Math 88 1 Amit 19 Commerce 92 2 Aishwarya 20 Arts 95 3 Priyanka 18 Biology 70 Iterating over rows using apply function : 0 Ankit 88 1 Amit 92 2 Aishwarya 95 3 Priyanka 70 dtype: object>