Copyright 2019 - Matt Harrison
@__mharrison__
""" | |
This is a module docstring. It must be at the TOP | |
of the file. | |
This is the markov module. You can create | |
a markov chain like this: | |
>>> m = Markov('ab') | |
>>> m.predict('a') | |
'b' |
%%javascript | |
var selectedCell = 0; | |
var viewOutput = false; | |
Jupyter.keyboard_manager.command_shortcuts.add_shortcut('ctrl-l', function (event) { | |
function getOutputScrollValue(cell) { | |
var percent = 0; | |
var ct = cell.output_area.element.offset().top; | |
var sme = Jupyter.notebook.scroll_manager.element; |
import argparse | |
import sys | |
import black | |
from blib2to3.pgen2.tokenize import TokenError | |
TEST_DATA = """ | |
Normal |
mush_df = pd.read_csv('../data/agaricus-lepiota.data.txt', | |
names='class,cap_shape,cap_surface,cap_color,bruises,' | |
'odor,g_attachment,g_spacing,g_size,g_color,s_shape,' | |
's_root,s_surface_a,s_surface_b,s_color_a,s_color_b,' | |
'v_type,v_color,ring_num,ring_type,spore_color,pop,hab'.split(',')) | |
mush_df = pd.get_dummies(mush_df, columns=mush_df.columns).drop(['class_e'],axis=1) |
cols = 'class,cap_shape,cap_surface,cap_color,bruises,'\ | |
'odor,g_attachment,g_spacing,g_size,g_color,s_shape,'\ | |
's_root,s_surface_a,s_surface_b,s_color_a,s_color_b,'\ | |
'v_type,v_color,ring_num,ring_type,spore_color,pop,hab'.split(',') | |
mush_df = pd.get_dummies(pd.read_csv('../data/agaricus-lepiota.data.txt', names=cols)) | |
mush_df |
# Data transformation from previous notebook | |
# col names in tao-all2.col from website | |
names = '''obs | |
year | |
month | |
day | |
date | |
latitude | |
longitude | |
zon.winds |
# Data transformation from previous notebook | |
# col names in tao-all2.col from website | |
names = '''obs | |
year | |
month | |
day | |
date | |
latitude | |
longitude | |
zon.winds |
%%time | |
cols = ['obs', 'year', 'month', 'day', 'date', 'latitude', 'longitude', | |
'zon.winds', 'mer.winds', 'humidity', 'air temp.', 's.s.temp.'] | |
nino = pd.read_csv('data/tao-all2.dat.gz', sep=' ', names=cols, header=None, | |
na_values='.', parse_dates=[[1,2,3]]) | |
cols = [c.strip().rstrip('.').replace(' ', '_').replace('.', '_') | |
for c in nino.columns] | |
nino.columns = cols | |
nino.date = pd.to_datetime(nino.date, format='%y%m%d') | |
nino['zon_winds_mph'] = nino.zon_winds * 2.237 |
===================== | |
Pytest Introduction | |
===================== | |
.. export PS1="$ " | |
Copyright 2018 - Matt Harrison | |
@__mharrison__ |