How to Select Rows with Head and Tail in Pandas

You may use Pandas functions head() and tail() in order to show first and last N rows of a DataFrame simultaneously. Let's review several ways to combine head() and tail functionality.

Can we use head and tail as one Pandas Function? The answer is yes! Check Step 3.

Step 1: Create a Sample DataFrame

Let's use this example DataFrame for this article:

import pandas as pd
data = {'productivity': [80, 20, 60, 30, 50, 55, 95],
        'salary': [3500, 1500, 2000, 1000, 2000, 1500, 4000],
        'age': [25, 30, 40, 35, 20, 40, 22]}
data_ix = ['Tim', 'Jim', 'Kim', 'Bim', 'Dim', 'Sim', 'Lim']
df = pd.DataFrame(data, index=data_ix)
productivity salary age
Tim 80 3500 25
Jim 20 1500 30
Kim 60 2000 40
Bim 30 1000 35
Dim 50 2000 20
Sim 55 1500 40
Lim 95 4000 22

Step 2: Pandas head() and tail() together

The easiest and simplest way to show the first and last N rows of a DataFrame in Pandas is by appending functions head and tail:

rows = 2
df.head(rows).append(df.tail(rows))

The result is:

productivity salary age
Tim 80 3500 25
Jim 20 1500 30
Sim 55 1500 40
Lim 95 4000 22

Step 3: head() and tail() function iloc

The second option is to use the function iloc which simulates a combination of head() and tail behavior. Let's show the first 2 rows and the one from the sample DataFrame:

import numpy as np
df.iloc[np.r_[0:2, -1:0]]

The result is:

productivity salary age
Tim 80 3500 25
Jim 20 1500 30
Lim 95 4000 22

Step 4: Show First and Last Rows with pd.option_context

One more way is available to show rows from the beginning and the end at the same time - pd.option_context. Let say that we want to show first and last 2 rows from a DataFrame - then we can use 'display.max_rows',4 which is going to show only 4 rows - equally selected from the start and the end of a DataFrame:

with pd.option_context('display.max_rows',4):
    print(df)

the output is:

productivity salary age
Tim 80 3500 25
Jim 20 1500 30
.. ... ... ...
Sim 55 1500 40
Lim 95 4000 22

[7 rows x 3 columns]

Note: This works only for even numbers.

Step 5: Pandas head(), tail and middle

The final option which is described here includes function concat and row selection by slicing. This technique and iloc allows showing asymmetric combination of first and last rows of a DataFrame:

pd.concat([df[:1], df[-2:]])
productivity salary age
Tim 80 3500 25
Sim 55 1500 40
Lim 95 4000 22

Now if we need to add a row from the middle of our DataFrame than we can use shape and floor division in order to calculate the middle and then we can concatenate it to the rest by:

start = 1
mid = df.shape[0]//2
mid_end = mid + 1
end = 2
pd.concat([df[:start], df[mid:mid_end], df[-end:]])

the output is:

productivity salary age
Tim 80 3500 25
Bim 30 1000 35
Sim 55 1500 40
Lim 95 4000 22

Those are just several examples which might be useful to display your DataFrame in the way you like it.

One more option is to combine head(), tail() and sample in order to get: first, last and some random rows. Below we can see how to get the first, the last and two random rows:

pd.concat([df[:1], df.sample(2), df[-1:]])
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