Coding Ref

In Pandas, the `head()`

method is used to return the first few rows of a DataFrame. This method is often used to quickly inspect the data in a DataFrame, or to get a sense of the data before performing more detailed analyses.

To use the `head()`

method, we first need to import the Pandas library and create a `DataFrame`

object.

Here is an example of how to use the `head()`

method to return the first few rows of a DataFrame:

main.py

```
import pandas as pd
# Create a DataFrame
df = pd.DataFrame({'A': [1, 2, 3, 4, 5, 6, 7, 8], 'B': [9, 10, 11, 12, 13, 14, 15, 16]})
# Use head() to return the first few rows
print(df.head())
```

output

```
A B
0 1 9
1 2 10
2 3 11
3 4 12
4 5 13
```

This will return the first five rows of the `DataFrame`

, with the column names as the row labels and the values in each row as the column values.

If the `DataFrame`

has fewer than five rows, `head()`

will return all the rows in the `DataFrame`

.

To customize the result, we can use the optional `n`

parameter of the `head()`

method.

This parameter specifies the number of rows to return, and if it is not specified, the default value is five.

Here is an example of how to use the `n`

parameter to specify the number of rows to return:

main.py

```
# Use head() to return the first two rows
print(df.head(2))
```

output

```
A B
0 1 9
1 2 10
```

In addition to returning the first few rows of a `DataFrame`

, the `head()`

method can also be used to return the first few rows of a `Series`

.

To do this, we can use the `head()`

method on the `Series`

object, in the same way as we would use it on a `DataFrame`

.

Here is an example:

main.py

```
# Create a Series
s = pd.Series([10, 20, 30, 40, 50])
# Use head() to return the first few rows
print(s.head())
```

output

```
0 10
1 20
2 30
3 40
4 50
dtype: int64
```

This will return the first five elements of the `Series`

, with the index labels as the row labels and the values as the column values.

If the `Series`

has fewer than five elements, `head()`

will return all the elements in the `Series`

.

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