Robert Samarek data4sci

## pandas_profiling.py
import pandas as pd
import numpy as np
#from ipywidgets import widgets
from pandas_profiling import ProfileReport
#from pandas_profiling.utils.cache import cache_file
profile = ProfileReport(df, title="#### Title ####", html={'style': {'full_width': True}}, sort="None")
# HTML report in a iframe
profile.to_notebook_iframe()
# nebo samotné `profile` také funguje
profile

## import.py
sys.path.append("/etc/scripts/etl/etl_scripts/")
from etl_utils_package.edison import edison_connect, edison_programy2df
from etl_utils_package.dwh import conn_close

## fuzzy.py
import fuzzymatcher
left_on = ["Facility Name", "Address", "City", "State"]
right_on = [
    "Provider Name", "Provider Street Address", "Provider City",
    "Provider State"
]
matched_results = fuzzymatcher.fuzzy_left_join(hospital_accounts,
                                            hospital_reimbursement,
                                            left_on,
                                            right_on,

## applymap.py
def color_neprijat_red(val):
    color = 'red' if val == 'Nepřijat' else 'black'
    return 'color: %s' % color

df.style.applymap(color_neprijat_red)

## comma_sep_list.py
cisla = df.groupby(['ID_PERSON'])['CISLO_PRIHLASKY'].apply(lambda x: ', '.join(x))

#obecně:

df.groupby("content_id")['tag'].apply(lambda tags: ','.join(tags))

## scatter_matrix.py
grr = pd.plotting.scatter_matrix(df, figsize=(15, 15), marker='o')

# nebo

import seaborn as sns
sns.pairplot(piv, kind = "reg")
plt.show()

## co_occurence.py
coocc = df.T.dot(df)
#optionaly - fill diagonal with 0s
np.fill_diagonal(coocc.values, 0)

## monitor.sh
$ cvt -r -v 3200 1800  60
# 3200x1800 59.94 Hz (CVT 5.76M9-R) hsync: 111.01 kHz; pclk: 373.00 MHz
Modeline "3200x1800R"  373.00  3200 3248 3280 3360  1800 1803 1808 1852 +hsync -vsync

$ xrandr --newmode "3200x1800R"  373.00  3200 3248 3280 3360  1800 1803 1808 1852 +hsync -vsync

$ xrandr --addmode eDP-1 3200x1800R

#$ xrandr --output eDP-1 --mode 3200x1800R

## sys_info.sh
inxi -Fxz

## clone_to_folder.sh
git clone git@gitlab.vsb.cz:sam029/p000-sam029-test.git temp
mv temp/.git test/.git
rm -rf temp
	import pandas as pd
	import numpy as np
	#from ipywidgets import widgets
	from pandas_profiling import ProfileReport
	#from pandas_profiling.utils.cache import cache_file
	profile = ProfileReport(df, title="#### Title ####", html={'style': {'full_width': True}}, sort="None")
	# HTML report in a iframe
	profile.to_notebook_iframe()
	# nebo samotné `profile` také funguje
	profile
	sys.path.append("/etc/scripts/etl/etl_scripts/")
	from etl_utils_package.edison import edison_connect, edison_programy2df
	from etl_utils_package.dwh import conn_close
	import fuzzymatcher
	left_on = ["Facility Name", "Address", "City", "State"]
	right_on = [
	"Provider Name", "Provider Street Address", "Provider City",
	"Provider State"
	]
	matched_results = fuzzymatcher.fuzzy_left_join(hospital_accounts,
	hospital_reimbursement,
	left_on,
	right_on,
	def color_neprijat_red(val):
	color = 'red' if val == 'Nepřijat' else 'black'
	return 'color: %s' % color

	df.style.applymap(color_neprijat_red)
	cisla = df.groupby(['ID_PERSON'])['CISLO_PRIHLASKY'].apply(lambda x: ', '.join(x))

	#obecně:

	df.groupby("content_id")['tag'].apply(lambda tags: ','.join(tags))
	grr = pd.plotting.scatter_matrix(df, figsize=(15, 15), marker='o')

	# nebo

	import seaborn as sns
	sns.pairplot(piv, kind = "reg")
	plt.show()
	coocc = df.T.dot(df)
	#optionaly - fill diagonal with 0s
	np.fill_diagonal(coocc.values, 0)
	$ cvt -r -v 3200 1800 60
	# 3200x1800 59.94 Hz (CVT 5.76M9-R) hsync: 111.01 kHz; pclk: 373.00 MHz
	Modeline "3200x1800R" 373.00 3200 3248 3280 3360 1800 1803 1808 1852 +hsync -vsync

	$ xrandr --newmode "3200x1800R" 373.00 3200 3248 3280 3360 1800 1803 1808 1852 +hsync -vsync

	$ xrandr --addmode eDP-1 3200x1800R

	#$ xrandr --output eDP-1 --mode 3200x1800R
	git clone git@gitlab.vsb.cz:sam029/p000-sam029-test.git temp
	mv temp/.git test/.git
	rm -rf temp