pandas loop through rows
for index, row in df.iterrows():
print(row['c1'], row['c2'])
Output:
10 100
11 110
12 120pandas loop through rows
for index, row in df.iterrows():
print(row['c1'], row['c2'])
Output:
10 100
11 110
12 120pandas iterate rows
import pandas as pd
import numpy as np
df = pd.DataFrame({'c1': [10, 11, 12], 'c2': [100, 110, 120]})
for index, row in df.iterrows():
print(row['c1'], row['c2'])python loop through column in dataframe
# Iterate over two given columns only from the dataframe
for column in empDfObj[['Name', 'City']]:
# Select column contents by column name using [] operator
columnSeriesObj = empDfObj[column]
print('Colunm Name : ', column)
print('Column Contents : ', columnSeriesObj.values)dataframe for loop
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 :\n", df)
print("\nIterating over rows using iterrows() method :\n")
# iterate through each row and select
# 'Name' and 'Age' column respectively.
for index, row in df.iterrows():
print (row["Name"], row["Age"])Copyright © 2021 Codeinu
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