The Python shape method returns a `tuple`

denoting the dimensions of a Python object on which it is applied. These Python objects on which the `shape`

method is applied is usually a `numpy.array`

or a `pandas.DataFrame`

. The number of elements in the tuple returned by the `shape`

method is equal to the number of dimensions in the Python object. Each `tuple`

element represents the number of elements corresponding to that dimension of the Python object.

## Pandas: shape method

The `shape`

method in **Pandas **returns a `tuple`

representing the dimensions i.e. **(rows & columns)** of the `DataFrame`

.

### 1. Check the dimensions of a DataFrame

```
# Import Pandas Python module
import pandas as pd
# Create a Python list
ls =[['A','B','C','D'], ['e' ,'f' ,'g' ,'h'], [11, 22, 33, 44]]
# Create a Pandas DataFrame from the above list
df = pd.DataFrame(ls)
# Print the DataFrame
print(df)
# Check the dimensions of the DataFrame
print(df.shape)
```

**Output:**

```
0 1 2 3
0 A B C D
1 e f g h
2 11 22 33 44
(3, 4)
```

The `shape`

method has returned a tuple **(3, 4)** with two elements depicting the DataFrame has two dimensions with three rows and four columns.

### 2. Check the dimensions of an empty DataFrame

```
# Import Pandas Python module
import pandas as pd
# Create an empty Pandas DataFrame
df = pd.DataFrame()
# Print the DataFrame
print(df)
# Check the dimensions of the empty DataFrame
print(df.shape)
```

**Output:**

```
Empty DataFrame
Columns: []
Index: []
(0, 0)
```

The `shape`

method has returned a tuple **(0, 0)** with two elements depicting the DataFrame has two dimensions with zero rows and zero columns.

## NumPy: shape method

The `shape`

method in **NumPy **returns a `tuple`

representing the dimensions of the `numpy array`

.

### 1. Check the dimensions of a numpy array

```
# Import Python NumPy module
import numpy as np
# Define a numpy array with zero dimensions
arr = np.array([[[1,2] ,[3,5]], [[2,3] ,[4,7]], [[3,4] ,[5,8]]])
# Print the numpy array
print(arr)
# Check the dimensions of arr
print(arr.shape)
```

**Output:**

```
[[[1 2 3]
[3 5 6]]]
(1, 2, 3)
```

The `shape`

method has returned a tuple **(1, 2, 3)** with three elements depicting the array has three dimensions where each dimension has one, two, and three elements respectively.

### 2. Check the dimensions of a numpy array with zero dimensions

```
# Import Python NumPy module
import numpy as np
# Define a numpy array with zero dimensions
arr = np.array(0)
# Print the numpy array
print(arr)
# Check the dimensions of arr
print(arr.shape)
```

**Output:**

```
0
()
```

The `shape`

method has returned an empty tuple **()** with zero elements depicting the array has zero dimensions.

### 3. Check the dimensions of a numpy array with one dimension but zero elements

```
# Import Python NumPy module
import numpy as np
# Define a numpy array from an empty list
arr = np.array([])
# Print the numpy array
print(arr)
# Check the dimensions of arr
print(arr.shape)
```

**Output:**

```
[]
(0,)
```

The `shape`

method has returned a tuple **(0,)** with one element depicting the array has only one dimension with zero elements.

## Summing-up

In this tutorial, we have learned how to use the `shape`

method in Python to find out the dimensions of the Python object (NumPy array or Pandas DataFrame).