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Python Pandas Exercises

Pandas Practice Set-1: Read rows in which the ‘cut’ is ‘Premium’, column ‘color’ of diamonds DataFrame

Pandas Practice Set-1: Exercise-54 with Solution

Write a Pandas program to read rows in which the ‘cut’ is ‘Premium’, column ‘color’ 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 in which the ‘cut’  is ‘Premium’, column ‘color’:")
print(diamonds.loc[diamonds.cut=='Premium', 'color'])

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 in which the ‘cut’  is ‘Premium’, column ‘color’:
1        E
3        I
12       F
14       E
15       E
26       I
45       F
53       E
54       D
56       J
61       D
64       I
68       G
69       E
72       H
73       H
85       G
86       H
87       H
88       H
89       I
99       H
101      E
103      G
106      G
112      I
116      F
125      F
126      H
135      E
        ..
53827    E
53834    E
53835    G
53836    D
53853    F
53856    D
53857    D
53859    E
53860    D
53861    D
53862    E
53867    G
53868    F
53871    F
53872    H
53877    F
53880    G
53888    G
53901    E
53904    E
53905    E
53910    E
53911    E
53912    F
53918    I
53928    E
53930    E
53931    F
53934    D
53938    H
Name: color, Length: 13791, dtype: object

Python Code Editor:


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Previous:Write a Pandas program to read rows 0 through 2 (inclusive), columns ‘color’ through ‘price’ (inclusive) of diamonds DataFrame.
Next: Write a Pandas program to read rows in positions 0 and 1, columns in positions 0 and 3 of diamonds DataFrame.

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