import pandas as pd import numpy as np info = pd.DataFrame(np.random.randn(4,2),columns = ['col1','col2']) for row_index,row in info.iterrows(): print (row_index,row) Output0 name John degree B.Techscore 90Name: 0, dtype: object1 name Smithdegree B.Comscore 40Name: 1, dtype: object2 name Alexanderdegree M.Comscore 80Name: 2, dtype: object3 name Williamdegree M.Techscore 98Name: 3, dtype: object
Question
import pandas as pd import numpy as np info = pd.DataFrame(np.random.randn(4,2),columns = ['col1','col2']) for row_index,row in info.iterrows(): print (row_index,row) Output0 name John degree B.Techscore 90Name: 0, dtype: object1 name Smithdegree B.Comscore 40Name: 1, dtype: object2 name Alexanderdegree M.Comscore 80Name: 2, dtype: object3 name Williamdegree M.Techscore 98Name: 3, dtype: object
Solution
The code you've posted is written in Python, specifically using the pandas and numpy libraries. It creates a DataFrame with random values, then iterates over the DataFrame rows, printing the index and row data for each.
However, the output you've provided doesn't seem to match the code. The output suggests a DataFrame with columns 'name', 'degree', and 'score', but the code creates a DataFrame with columns 'col1' and 'col2' and random values.
If you want to create a DataFrame similar to the output, you can use the following code:
import pandas as pd
data = {'name': ['John', 'Smith', 'Alexander', 'William'],
'degree': ['B.Tech', 'B.Com', 'M.Com', 'M.Tech'],
'score': [90, 40, 80, 98]}
df = pd.DataFrame(data)
for row_index, row in df.iterrows():
print(row_index, row)
This will create a DataFrame with the specified 'name', 'degree', and 'score' data, then iterate over the DataFrame rows, printing the index and row data for each.
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