# Python Numpy1 array

### Contents

• Import Numpy
• Create 1 dim array
• Numpy array methods

### Import Numpy

```import numpy as np
```

After this, you can use numpy as np

np.xxxx

First time, it take times to load numpy library (only first time)

### Create 1 dim array

#### We can create Numpy array from Python array

```data = np.array([1,2,3,4,5,6,7,8,0,10])
print(data)
print(data.dtype)  # int64

```

#### Fill Zero

```a = np.zeros(3)
print(a)
```

#### Fill one

```b = np.ones(3)
print(b)
```

#### Convert type in array

```a = np.array([1.0, 1.5, 2.0])
e = np.array(a, dtype=complex)
print(e.dtype)
```

### Numpy array methods

#### Dimension

```# Dimension
data = np.array([1,2,3,4,5,6,7,8,0,10])
print('Dim:', data.ndim)
```

#### Size

```# Size
data = np.array([1,2,3,4,5,6,7,8,0,10])
print('Size:', data.size)
```

#### Sort

```# Sort
data = np.array([10, 9, 8, 7, 6, 5, 4, 3, 1, 6])
data.sort()
print(data)  # [ 1  3  4  5  6  6  7  8  9 10]
```

#### Reverse

```# Reverse
data = np.array([10, 9, 8, 7, 6, 5, 4, 3, 1, 6])
data[::-1].sort() # Sort : [ 1  3  4  5  6  6  7  8  9 10] and Reverse
print(data)  # [10  9  8  7  6  6  5  4  3  1]
```

#### Max

```data = np.array([10, 9, 8, 7, 6, 5, 4, 3, 1, 6])
print('Max:', data.max())
```

#### Total

```# Total
data = np.array([10, 9, 8, 7, 6, 5, 4, 3, 1, 6])
print('Sum:', data.sum())
```

#### Cum

```# Cum
data = np.array([10, 9, 8, 7, 6, 5, 4, 3, 1, 6])
print('Cum:', data.cumsum())
```
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