Using iloc to filter rows in Python

In this blog we will look at how we can leverage iloc to access specific rows in a data frame¶

Step 1: Import the libraries¶

In [1]:

import pandas as pd
import numpy as np

Step 2:Creating the Data Frame¶

In [10]:

Day=['Day '+ str(i+1) for i in range(10)]
Day

Out[10]:

['Day 1',
 'Day 2',
 'Day 3',
 'Day 4',
 'Day 5',
 'Day 6',
 'Day 7',
 'Day 8',
 'Day 9',
 'Day 10']

In [14]:

df = pd.DataFrame(Day)
df['Random_Values']=np.random.rand(10)
df.columns=['Day','Random_Values']
df

Out[14]:

	Day	Random_Values
0	Day 1	0.780147
1	Day 2	0.726025
2	Day 3	0.960263
3	Day 4	0.445348
4	Day 5	0.148012
5	Day 6	0.219381
6	Day 7	0.287973
7	Day 8	0.403218
8	Day 9	0.607353
9	Day 10	0.415898

Step 3:Using iloc to access rows between 3 and 5¶

In [15]:

df.iloc[3:6]

Out[15]:

	Day	Random_Values
3	Day 4	0.445348
4	Day 5	0.148012
5	Day 6	0.219381

Step 4: Accessing specific column while using iloc¶

In [16]:

df.iloc[3:6]['Day']

Out[16]:

3    Day 4
4    Day 5
5    Day 6
Name: Day, dtype: object