# [PYTHON] Data handling

## What is NumPy

numpy is a library for efficient numerical calculation in the Python language. numpy has the following advantages: --High-speed calculation using vectorization notation --Efficient descriptive statistical data manipulation --Condition description in the audience

## ndarray: Multidimensional placement object

In ndarray, vectorization notation enables high-speed batch calculation for arrays.

### Creation of ndarray object

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#### `ndarray.py`

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#### **`ndarray1.py`**
```python

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import numpy as np
ndarray1 = np.array([1,2,3,4,5])
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print(ndarray)
# Output result [1 2 3 4 5]
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print(ndarray1)
``````

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#### `Output result`

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[1 2 3 4 5]
``````

#### `ndarray2.py`

``````
ndarray2 = np.arrange(1,6,1)
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print(ndarray2)
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# Output result [1 2 3 4 5]

print(np.ones(5))
# Output result [1 1 1 1 1]

``````

np.The array function can pass a multidimensional list.

#### `ndarry2.py`

``````
ndarray4 = np.array([[1,2,3],[4,5,6]])
print(ndarray4)

# Output result [[1 2 3] [4 5 6]]
``````

-shape → shape of the array -size → Total number of elements in the array -ndim → Number of dimensions of array

#### ` ndarray3.py`

``````
ndarray = np.array([[1, 2, 3], [4, 5, 6]])
print(ndarray.shape)
print(ndarray.size)
print(ndarray.ndim)
# Output result (2,3)
# Output result 6
# Output result 2
``````

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``````

#### **`Output result`**
```text

[1 2 3 4 5]
``````

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