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``` ```
## for statement
```
words = ['cat', 'window', 'defenestrate']
for w in words:
print(w, len(w))
```
```
for i in range(5):
print(i)
```
```
a = ['Mary', 'had', 'a', 'little', 'lamb']
for i in range(len(a)):
print(i, a[i])
```
# Numpy arrays
Numpy, on the other hand, is a core Python library for scientific computation (hence the name “Numeric Python” or Numpy). The library provides methods and functions to create and work with multi-dimensional objects called arrays. Arrays are grids of values, and unlike Python lists, they are of the same data type:
```
# 1-dimesional array
array([1, 2, 3])
# 2-dimensional array
array([[1, 2],
[3, 4],
[5, 6]])
```
# Matplotlib
Matplotlib is a 2d plotting library which produces publication quality figures in a variety of hardcopy formats and interactive environments. Matplotlib can be used in Python scripts, Python and IPython shell, Jupyter Notebook, web application servers and GUI toolkits.
matplotlib.pyplot is a collection of functions that make matplotlib work like MATLAB. Majority of plotting commands in pyplot have MATLAB analogs with similar arguments. Let us take a couple of examples:
```
import matplotlib.pyplot as plt
plt.plot([1,2,3,4])
plt.ylabel('some numbers')
plt.show()
```
```
import matplotlib.pyplot as plt
>>> x = [21,22,23,4,5,6,77,8,9,10,31,32,33,34,35,36,37,18,49,50,100]
>>> num_bins = 5
>>> plt.hist(x, num_bins, facecolor='blue')
>>> plt.show()
```
# References # References
[^1]: https://developers.google.com/edu/python/introduction [^1]: https://developers.google.com/edu/python/introduction

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