În acest articol, vom acoperi cum să iterați peste rânduri dintr-un DataFrame în Pandas .
Cum se repetă peste rânduri dintr-un DataFrame în Pandas
Python este un limbaj excelent pentru analiza datelor, în primul rând datorită ecosistemului fantastic al pachetelor Python centrate pe date. panda este unul dintre acele pachete și facilitează mult importarea și analiza datelor.
Să vedem diferitele moduri de a repeta peste rânduri în Pandas Cadrul de date :
Metoda 1: Utilizarea atributului index al Dataframe-ului.
Python3
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# 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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Ieșire:
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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>
Metoda 2: Folosind loc[] funcţie a cadrului de date.
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 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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Ieșire:
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>
Metoda 3: Folosind iloc[] funcţie al DataFrame-ului.
Python3
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# 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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Ieșire:
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 >
Metoda 4: Folosind interrows() metodă a cadrului de date.
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 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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Ieșire:
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>
Metoda 5: Folosind itertupluri() metoda Dataframe-ului.
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'>))> |
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Ieșire:
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 >
Metoda 6: Folosind aplica() metodă a cadrului de date.
Python3
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# 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>))> |
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Ieșire:
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>