In [1]:
1+1
Out[1]:
2
In [2]:
_1*3
Out[2]:
6
Como trabajar con NUMPY¶
In [3]:
import numpy as np
A = np.array([[1, 2, 3, 4], [5, 6, 7, 8], [9,10, 11, 12]])
print(A)
print(type(A))
[[ 1 2 3 4] [ 5 6 7 8] [ 9 10 11 12]] <class 'numpy.ndarray'>
Como trabajar con PANDAS¶
In [4]:
import pandas as pd
dat_csv = pd.read_csv('empleados.csv', encoding = "ISO-8859-1")
dat_csv
Out[4]:
| id | Nombre | Sexo | Sueldo | |
|---|---|---|---|---|
| 0 | 1 | Juan | m | 10000 |
| 1 | 2 | Ramón | m | 20000 |
| 2 | 3 | Anna | f | 10500 |
| 3 | 4 | Julieta | f | 13000 |
| 4 | 5 | Pablo | m | 30000 |
| 5 | 6 | Pedro | m | 10500 |
| 6 | 7 | Gaby | f | 11000 |
| 7 | 8 | Cecilia | f | 27000 |
Como trabajar con MATPLOTLIB¶
In [5]:
import matplotlib.pyplot as plt
x = list(range(-4 , 6))
y = [i**2 for i in x]
plt.plot(x,y)
plt.show
Out[5]:
<function matplotlib.pyplot.show(close=None, block=None)>
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