gustheman

print(len("✋"))
print(len("✋🏾"))
print(len("👪"))
print(len("👨‍👨‍👧‍👦"))
print(len("👨‍👧‍👦"))
print(len("👨‍👦"))

gustheman

print('this is Python file to test some magics')

def my_function(a, b, c):
  print(a, b, c)
  return a + b + c

gustheman

import pandas as pd
import numpy as np
import plotly.express as px

df = pd.read_csv("kaggle_survey_2022_responses.csv")

def plot_answers(data, question_prefix, year):
  filter_columns = [col for col in data.columns if col.startswith(question_prefix)]
  df = data[filter_columns]
  

gustheman

import matplotlib.pyplot as plt
import numpy as np

plt.figure(figsize=(14,10))

def show_frequency(x, y, i):
  plt.subplot(3, 1, i)
  plt.stem(x, y, 'r', use_line_collection=True)
  plt.plot(x, y)
  plt.xlabel("time")

gustheman

!pip install -q "tensorflow_io==0.28.*"

!curl -O https://storage.googleapis.com/audioset/miaow_16k.wav

import tensorflow as tf
import tensorflow_io as tfio
from IPython.display import Audio

audio = tfio.audio.AudioIOTensor('miaow_16k.wav')

gustheman

import matplotlib.pyplot as plt
import tensorflow as tf

n = len(x)
T = 1/samples

yf = tf.signal.fft(ys)
xf = np.linspace(0.0, 1.0/(2.0*T), int(n/2))

plt.plot(xf, 2.0/n*np.abs(yf[:n//2]))

gustheman

import tensorflow as tf
import tensorflow_io as tfio

tensor = tf.cast(audio_tensor, tf.float32) / 32768.0

spectrogram = tfio.audio.spectrogram(
    tensor, nfft=512, window=512, stride=256)

mel_spectrogram= tfio.audio.melscale(
    spectrogram, rate=16000, mels=128, fmin=0, fmax=8000)