Ze1598

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

import azure.cognitiveservices.speech as speechsdk

subscription_key = "your_key"
speech_region = "your_region"

speech_config = speechsdk.SpeechConfig(subscription_key, speech_region)

Ze1598

from moviepy.editor import VideoFileClip

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

Ze1598

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

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

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

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

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

Ze1598

import pandas as pd
import numpy as np

def generate_random_dates(num_dates: int) -> np.array:
	"""Generate a 1D array of `num_dates` random dates.
	"""
	start_date = "2020-01-01"
	# Generate all days for 2020
	available_dates = [np.datetime64(start_date) + days for days in range(365)]
	# Get `num_dates` random dates from 2020

Ze1598

import pandas as pd
import matplotlib.pyplot as plt
import numpy as np

# Load the CSV (load date data as proper date types)
df = pd.read_csv("page_views.csv")
df["date"] = pd.to_datetime(df["date"])
# Sort the DF from oldest to most recent recordings
df.sort_values(by="date", inplace=True)
# Use the column of dates as the DF's index