Viewing first rows

The head() method returns the first n rows of a DataFrame; default n=5.

head, tail, info

When you open a new dataset, the first thing is to look at it:

df.head()        # first 5 rows
df.head(2)       # first 2 rows
df.tail(3)       # last 3 rows
df.info()        # column types and non-null counts

info() immediately shows missing values and columns read with the wrong type (for example text instead of numbers).

describe and value_counts

A summary of numeric columns is taken with describe(), the distribution of categorical columns with value_counts():

df.describe()                 # count, mean, std, min, quartiles, max
df["sehir"].value_counts()    # how often each value appears
df["yas"].nunique()           # number of distinct values

In classification problems, applying value_counts() to the label column shows whether the classes are balanced.

Exercise Get to know the data

Find how often each city appears in the sehir column with value_counts() and print the count of the most frequent city. Then print the length of the first 2 rows with len(df.head(2)).

Show example solution

import pandas as pd

df = pd.DataFrame({"sehir": ["Ankara", "İzmir", "Ankara", "Bursa", "Ankara"]})

sayim = df["sehir"].value_counts()
print(sayim.max())
print(len(df.head(2)))

Test yourself

How many rows does <code>df.head()</code> show without an argument?
- All
- 5
- 10
- 1
Show answer

5 — The default value of n is 5.
Show the last 3 rows.
```
print(df.____(3))
```
Show answer
```
print(df.tail(3))
```
Match the methods.

head()

First rows
info()

Column types
describe()

Numeric summary
value_counts()

Value frequencies

Next lesson: Summary - Pandas basics

We Are Enhancing Your Experience

Cookie Preferences

Strictly Necessary Cookies

Analytical Cookies