Python dict ndarray

 It seems like there might be a little confusion in your question. In Python, `dict` is a built-in data type that stores a collection of key-value pairs. On the other hand, `ndarray` (often just referred to as an array) is a type provided by the `NumPy` library that represents a multi-dimensional, homogeneous array of fixed-size items.


I assume you're looking for examples that showcase both. Here's a brief introduction:


### 1. Python `dict`:


```python

person = {

    "name": "John",

    "age": 30,

    "city": "New York"

}


print(person["name"])  # Outputs: John

```


### 2. `numpy ndarray`:


First, you need to install numpy:


```bash

pip install numpy

```


Then you can create arrays:


```python

import numpy as np


arr = np.array([1, 2, 3, 4, 5])

print(arr)            # Outputs: [1 2 3 4 5]

print(type(arr))      # Outputs: <class 'numpy.ndarray'>

```


### Combining both:


Here's an example of using a dictionary where the values are `ndarray` objects:


```python

import numpy as np


data = {

    "temperatures": np.array([22.5, 23.0, 23.5, 24.0, 22.0]),

    "humidity": np.array([0.55, 0.52, 0.53, 0.50, 0.51])

}


print(data["temperatures"])   # Outputs: [22.5 23.  23.5 24.  22. ]

print(data["humidity"])       # Outputs: [0.55 0.52 0.53 0.5  0.51]

```


In the above example, the dictionary `data` contains two keys, `"temperatures"` and `"humidity"`, and their corresponding values are `ndarray` objects containing related measurements.

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