pandas-in-jupyter.ipynb

Kernel: Python 2 (SageMath)

See 10 Minutes to pandas

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

s = pd.Series([1,3,5,np.nan,7,9])
s

0    1.0
1    3.0
2    5.0
3    NaN
4    7.0
5    9.0
dtype: float64

dates = pd.date_range('20130101', periods=6)
dates

DatetimeIndex(['2013-01-01', '2013-01-02', '2013-01-03', '2013-01-04',
               '2013-01-05', '2013-01-06'],
              dtype='datetime64[ns]', freq='D')

df = pd.DataFrame(np.random.randn(6,4), index=dates, columns=list('ABCD'))
df

	A	B	C	D
2013-01-01	-0.029417	0.882268	-0.978273	-0.663323
2013-01-02	0.254186	0.387478	0.703371	-0.021914
2013-01-03	0.513787	-1.004384	0.706066	-0.705586
2013-01-04	-0.857732	0.820974	-1.391208	-0.506392
2013-01-05	0.724756	-0.895884	-1.231815	-0.993212
2013-01-06	2.227114	1.765319	0.215122	-0.175127