%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
from scipy.stats import norm
def plot_sample():
x = np.linspace(-10, 10, 1000)
for sigma in range(1, 7):
plt.plot(x, norm.pdf(x, 0, sigma))
plot_sample()
import seaborn as sns
plot_sample()
set_style
color_palette
, set_palette
norm_data = norm.rvs(size=1000)
sns.distplot(norm_data, kde=False, fit=norm)
norm.fit(norm_data)
x = np.linspace(0,10,100)
y = x + norm.rvs(size=100)
sns.regplot(x, y)
import pandas as pd
import datetime as dt
def valstr_to_date(valstr):
t = float(valstr)
year = int(t)
seconds = int((t % 1) * 365 * 24 * 60 * 60)
return dt.datetime(year=year, month=1, day=1) + dt.timedelta(seconds=seconds)
data = pd.read_table('data/temperatures.txt', delim_whitespace=True, header=None, names=[ "Date", "Temperature" ], index_col=0, na_values=[ "99", "-99" ], date_parser=valstr_to_date)
data.head()
data.plot()
import matplotlib as mpl
mpl.use('pgf')
plot_sample()
plt.savefig("plots/vector_plot.pgf")
!tail plots/vector_plot.pgf