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Pandas Practice Set-1: Read rows 2 through 5 (inclusive), columns in positions 0 through 2 (exclusive) of diamonds DataFrame


58. Read Rows 2 Through 5 (Inclusive), Columns in Positions 0 Through 2 (Exclusive)

Write a Pandas program to read rows 2 through 5 (inclusive), columns in positions 0 through 2 (exclusive) of diamonds DataFrame.

Sample Solution:

Python Code:

import pandas as pd
diamonds = pd.read_csv('https://raw.githubusercontent.com/mwaskom/seaborn-data/master/diamonds.csv')
print("Original Dataframe:")
print(diamonds.head())
print("\nRows 2 through 5 (inclusive), columns in positions 0 through 2 (exclusive):")
print(diamonds.iloc[2:5, 0:2])

Sample Output:

Original Dataframe:
   carat      cut color clarity  depth  table  price     x     y     z
0   0.23    Ideal     E     SI2   61.5   55.0    326  3.95  3.98  2.43
1   0.21  Premium     E     SI1   59.8   61.0    326  3.89  3.84  2.31
2   0.23     Good     E     VS1   56.9   65.0    327  4.05  4.07  2.31
3   0.29  Premium     I     VS2   62.4   58.0    334  4.20  4.23  2.63
4   0.31     Good     J     SI2   63.3   58.0    335  4.34  4.35  2.75

Rows 2 through 5 (inclusive), columns in positions 0 through 2 (exclusive):
   carat      cut
2   0.23     Good
3   0.29  Premium
4   0.31     Good

For more Practice: Solve these Related Problems:

  • Write a Pandas program to use iloc to select rows 2 to 5 and columns 0 to 1 from the diamonds DataFrame.
  • Write a Pandas program to slice the diamonds DataFrame for rows 2 through 5 (inclusive) and the first two columns, then display the output.
  • Write a Pandas program to extract a block of data from the diamonds DataFrame using iloc with rows 2-5 and columns 0-1.
  • Write a Pandas program to load the diamonds CSV and retrieve rows 2 through 5 and columns up to but not including position 2 using positional indexing.

Go to:


Previous: Write a Pandas program to read rows in positions 0 through 4 (exclusive) and all columns of diamonds DataFrame.
Next: Write a Pandas program to print a concise summary of diamonds DataFrame.

Python Code Editor:

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