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Add one example #1

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22 changes: 20 additions & 2 deletions README.md
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Expand Up @@ -2,7 +2,7 @@

![image](https://github.com/guenchi/numpy/blob/gh-pages/img/NumPy.jpeg)

### and it's faster than the Native NumPy of Python
### and it's faster than the Native NumPy of Python-best example


```
Expand All @@ -25,8 +25,26 @@
(0.01745240643728351 0.03489949670250097 0.05233595624294383 0.0697564737441253
0.08715574274765817 0.10452846326765346 0.12186934340514748 0.13917310096006544)
```
#Example 2
# compare NumPy and native arrays
```
import numpy as np
import time

length = 10
native_lst = [i for i in range(length)]

numpy_lst = np.array(native_lst)
```
# find the speed difference
# use theperf_counter_ns() function instead of time()
# As I want the highest possible accuracy
```

time1 = time.perf_counter_ns()
time2 = time.perf_counter_ns()
print = time2 - time1
```
### Depencies:

https://guenchi.github.io/Darkart
Expand All @@ -45,4 +63,4 @@ https://guenchi.github.io/SymPy

https://guenchi.github.io/Matplotlib

https://guenchi.github.io/Pandas
https://guenchi.github.io/Pandas