Coding Ref

In Pandas, there are several ways to get the first row of a DataFrame.

Depending on the context and the data you are working with, you may want to get the first row in a DataFrame in a specific way.

We will go over the different ways to get the first row in Pandas, including how to customize the result and add labels and annotations.

`iloc[]`

To get the first row of a DataFrame in Pandas, we can use the `iloc[]`

method.

This method allows us to access the rows and columns of a DataFrame by their index position.

To get the first row of a DataFrame, we can use the following syntax:

main.py

```
import pandas as pd
# Create a DataFrame
df = pd.DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6]})
# Use iloc[] to get the first row
first_row = df.iloc[0]
```

output

```
A 1
B 4
Name: 0, dtype: int64
```

This will return a `Series`

object containing the data from the first row of the `DataFrame`

.

The `Series`

will have the same column names as the `DataFrame`

, and the values will be in the same order as they appear in the `DataFrame`

.

`loc[]`

To customize the result, we can use the `loc[]`

method instead of `iloc[]`

.

This method allows us to access the rows and columns of a DataFrame by their labels instead of their index position.

This can be useful when the index labels of the DataFrame are more meaningful than the index positions.

Here is an example of how to use the `loc[]`

method to get the first row of a DataFrame:

main.py

```
# Use loc[] to get the first row
first_row = df.loc[0]
```

output

```
A 1
B 4
Name: 0, dtype: int64
```

`head()`

In addition to getting the first row of a DataFrame, we can also use the `head()`

method to get the first few rows of a DataFrame.

This method takes an optional parameter, `n`

, which specifies the number of rows to return.

If `n`

is not specified, the `head()`

method will return the first five rows of the DataFrame.

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

method to get the first row of a DataFrame:

main.py

```
# Use head() to get the first row
first_row = df.head(1)
```

output

```
A B
0 1 4
```

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