How to generate timeseries using Pandas and Seaborn?
This recipe helps you generate timeseries using Pandas and Seaborn
In [2]:
## How to generate timeseries using Pandas and Seaborn
def Snippet_115():
print()
print(format('How to generate timeseries using Pandas and Seaborn','*^82'))
import warnings
warnings.filterwarnings("ignore")
# load libraries
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
data = {'date': ['2014-05-01 18:47:05.069722', '2014-05-01 18:47:05.119994',
'2014-05-02 18:47:05.178768', '2014-05-02 18:47:05.230071',
'2014-05-02 18:47:05.230071', '2014-05-02 18:47:05.280592',
'2014-05-03 18:47:05.332662', '2014-05-03 18:47:05.385109',
'2014-05-04 18:47:05.436523', '2014-05-04 18:47:05.486877'],
'deaths_regiment_1': [34, 43, 14, 15, 15, 14, 31, 25, 62, 41],
'deaths_regiment_2': [52, 66, 78, 15, 15, 5, 25, 25, 86, 1],
'deaths_regiment_3': [13, 73, 82, 58, 52, 87, 26, 5, 56, 75],
'deaths_regiment_4': [44, 75, 26, 15, 15, 14, 54, 25, 24, 72],
'deaths_regiment_5': [25, 24, 25, 15, 57, 68, 21, 27, 62, 5],
'deaths_regiment_6': [84, 84, 26, 15, 15, 14, 26, 25, 62, 24],
'deaths_regiment_7': [46, 57, 26, 15, 15, 14, 26, 25, 62, 41]}
df = pd.DataFrame(data, columns = ['date', 'battle_deaths', 'deaths_regiment_1',
'deaths_regiment_2', 'deaths_regiment_3', 'deaths_regiment_4',
'deaths_regiment_5', 'deaths_regiment_6', 'deaths_regiment_7'])
df = df.set_index(df.date)
# dataFrame
print(); print(df)
# Time Series Plot
sns.tsplot([df.deaths_regiment_1, df.deaths_regiment_2, df.deaths_regiment_3, df.deaths_regiment_4,
df.deaths_regiment_5, df.deaths_regiment_6, df.deaths_regiment_7])
plt.show()
Snippet_115()
In [ ]: