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 120iterate over rows dataframe
df = pd.DataFrame([{'c1':10, 'c2':100}, {'c1':11,'c2':110}, {'c1':12,'c2':120}])
for index, row in df.iterrows():
print(row['c1'], row['c2'])python - iterate with the data frame
# Option 1
for row in df.iterrows():
print row.loc[0,'A']
print row.A
print row.index()
# Option 2
for i in range(len(df)) :
print(df.iloc[i, 0], df.iloc[i, 2])pandas 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)how to iterate through a pandas dataframe
# creating a list of dataframe columns
columns = list(df)
for i in columns:
# printing the third element of the column
print (df[i][2])Copyright © 2021 Codeinu
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