José Fernando Costa Ze1598

data & analytics and process automation

Ze1598 / close_sticky_add.py

Last active July 28, 2021 18:36

Arknights - scrape operator level up stats

	from selenium import webdriver
	from webdriver_manager.chrome import ChromeDriverManager

	# Dynamically install a Chrome web driver and instantiate it
	driver = webdriver.Chrome(ChromeDriverManager().install())
	# Make the driver wait 7 seconds for the page to load
	driver.implicitly_wait(7)
	# Go the Phantom's character page
	driver.get("https://gamepress.gg/arknights/operator/phantom")
	# Element to scroll to

Ze1598 / idx_min_max.py

Created May 6, 2021 11:26

Find column with max/min value for each row in dataframe

	import pandas as pd

	# Working data
	data = [
	{
	"Symbol": "KLAC",
	"Company": "KLA Corporation",
	"Sector": "Information Technology",
	"Date": "2018-02-02",
	"Price": 99.11979699999999,

Ze1598 / transcribe_video_audio.py

Created January 28, 2021 11:01

Transcribe video audio using Azure Cognitive Services

	import azure.cognitiveservices.speech as speechsdk
	import time
	import pickle

	subscription_key = "your_key"
	speech_region = "your_region"
	file_name = "your_audio.wav"
	# Authenticate
	speech_config = speechsdk.SpeechConfig(subscription_key, speech_region)
	# Set up the file as the audio source

Ze1598 / cogn_serv_auth.py

Created January 28, 2021 10:58

Authenticate into Azure Cognitive Services through the Python SDK

	import azure.cognitiveservices.speech as speechsdk

	subscription_key = "your_key"
	speech_region = "your_region"

	speech_config = speechsdk.SpeechConfig(subscription_key, speech_region)

Ze1598 / extract_audio.py

Last active January 28, 2021 11:25

Extract audio from video

	from moviepy.editor import VideoFileClip

	video = VideoFileClip("your_video.mp4")
	audio = video.audio
	audio.write_audiofile("audio_only.wav")

Ze1598 / prog_languages.py

Last active January 24, 2021 21:19

Python Data Analysis Part 4: Programming Languages

	import pandas as pd
	from os import getcwd, path
	import plotly.express as px
	import plotly.offline as pyo
	pyo.init_notebook_mode()

	path_to_data = path.join(getcwd(), "data", "survey_results_public.csv")
	data = pd.read_csv(path_to_data)

	data = data[["LanguageWorkedWith"]]

Ze1598 / education.py

Last active January 24, 2021 18:59

Python Data Analysis Part 3: Education of Respondents

	import pandas as pd
	from os import getcwd, path
	import plotly.express as px
	import plotly.offline as pyo
	pyo.init_notebook_mode()

	path_to_data = path.join(getcwd(), "data", "survey_results_public.csv")
	data = pd.read_csv(path_to_data)

	data = data[["EdLevel"]]

Ze1598 / compensation.py

Last active January 24, 2021 17:39

Python Data Analysis Part 2: Annual Compensation

	import pandas as pd
	from os import getcwd, path
	import plotly.express as px
	import plotly.offline as pyo
	pyo.init_notebook_mode()

	path_to_data = path.join(getcwd(), "data", "survey_results_public.csv")
	data = pd.read_csv(path_to_data)

	data = data[["ConvertedComp"]]

Ze1598 / age.py

Created January 24, 2021 15:26

Python Data Analysis Part 1: Age of Respondents

	import pandas as pd
	from os import getcwd, path
	import plotly.express as px
	import plotly.offline as pyo
	pyo.init_notebook_mode()

	path_to_data = path.join(getcwd(), "data", "survey_results_public.csv")
	data = pd.read_csv(path_to_data)

	data = data[["Age"]]

Ze1598 / custom_mask.py

Created December 6, 2020 16:54

Create a custom shape mask with Python & Pillow

	from PIL import Image

	# Create a blank grey image
	wip_img = Image.new("RGBA", (550, 450), "#f2f2f2")
	# Load the santa hat
	santa_hat = Image.open("santa_hat.png")
	# At first this is just a black rectangle of the same size as the hat
	shadow = Image.new("RGBA", santa_hat.size, color="black")

	# Coordinates at which to draw the hat and shadow