Informatics Practices
How do you iterate over a dataframe? Explain with the help of code snippet.
Python Data Handling
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Answer
Iterating over rows in the DataFrame:
The iterrows() method is used to iterate over each row in the DataFrame. In this method, each horizontal subset is in the form of (row-index, series), where the series contains all column values for that row-index.
For example :
import pandas as pd
total_sales = {2015 : {'Qtr1' : 34500, 'Qtr2' : 45000},
2016 : {'Qtr1' : 44500, 'Qtr2' : 65000}}
df = pd.DataFrame(total_sales)
for (row, rowseries) in df.iterrows():
print("RowIndex :", row)
print('Containing :')
print(rowseries)
Output
RowIndex : Qtr1
Containing :
2015 34500
2016 44500
Name: Qtr1, dtype: int64
RowIndex : Qtr2
Containing :
2015 45000
2016 65000
Name: Qtr2, dtype: int64
Iterating over columns in the DataFrame:
The iteritems() method is used to iterate over each column in the DataFrame. In this method, each vertical subset is in the form of (column-index, series), where the series contains all row values for that column-index.
For example :
import pandas as pd
total_sales = {2015 : {'Qtr1' : 34500, 'Qtr2' : 45000},
2016 : {'Qtr1' : 44500, 'Qtr2' : 65000}}
df = pd.DataFrame(total_sales)
for (col, colseries) in df.iteritems():
print("Column Index :", col)
print('Containing :')
print(colseries)
Output
Column Index : 2015
Containing :
Qtr1 34500
Qtr2 45000
Name: 2015, dtype: int64
Column Index : 2016
Containing :
Qtr1 44500
Qtr2 65000
Name: 2016, dtype: int64
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