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Senior Applied Scientist

ravi Shankar ravi07bec

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Senior Applied Scientist
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@ravi07bec
ravi07bec / gtrends.py
Created October 29, 2020 06:41
from pytrends.request import TrendReq
url="https://trends.google.com/trends/explore?date=today%205-y&geo=US&q=dumbbells"
pytrends.build_payload(kw_list, cat=0, timeframe='today 5-y', geo='US', gprop='')
gtrends=pytrends.interest_over_time().reset_index()
test=px.scatter(gtrends,x='date',y=filters3,height=450,title="""<a href="{}">{}</a>""".format(url,filters3+":Google Searches-5 Years"))
test.update_traces(mode='lines+markers')
test.update_layout({
'plot_bgcolor': 'rgba(0, 0, 0, 0)',
@ravi07bec
ravi07bec / treechart.py
Created October 29, 2020 06:38
import plotly.graph_objects as go
from plotly.subplots import make_subplots
import pandas as pd
df1 = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/718417069ead87650b90472464c7565dc8c2cb1c/sunburst-coffee-flavors-complete.csv')
df2 = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/718417069ead87650b90472464c7565dc8c2cb1c/coffee-flavors.csv')
fig = make_subplots(
rows = 1, cols = 2,
@ravi07bec
ravi07bec / youtube.py
Created October 29, 2020 06:35
def embed_iframe(value):
print(value)
variant=value.split('\n')[0]
#print('https://www.youtube.com/watch?v=sh-MQboWJug')
df_final2=pd.read_csv('youtube_ids.csv')
print(df_final2)
df_final2['Variety']=df_final2['Variety'].str.upper()
@ravi07bec
ravi07bec / wordcloud.py
Last active October 29, 2020 06:33
stopwords = set(STOPWORDS)
import random
foo = ['black','white']
for i in variety:
subset=data[data['variety']==i]
subset['description']=subset['description'].str.lower()
subset['description2']=subset['description'].apply(lambda x: ' '.join([word for word in x.split() if word not in (stopwords)]))
text = " ".join(review for review in subset.description2)
wc = WordCloud(background_color=random.choice(foo), max_words=100, mask=transformed_wine_mask,
@ravi07bec
ravi07bec / tb.py
Created October 29, 2020 06:28
import os
import tensorflow as tf
from tensorflow.examples.tutorials.mnist import input_data
LOG_DIR = 'logs'
mnist = input_data.read_data_sets('MNIST_data')
images = tf.Variable(mnist.test.images, name='images')
with tf.Session() as sess:
@ravi07bec
ravi07bec / first_figure.html
Created October 24, 2020 14:30
This file has been truncated, but you can view the full file.
<html>
<head><meta charset="utf-8" /></head>
<body>
<div>
<script type="text/javascript">window.PlotlyConfig = {MathJaxConfig: 'local'};</script>
<script type="text/javascript">/**
* plotly.js v1.57.1
* Copyright 2012-2020, Plotly, Inc.
* All rights reserved.
@ravi07bec
ravi07bec / music_vector.json
Last active August 26, 2021 20:53
{
"embeddings": [
{
"tensorName": "music_vector",
"tensorShape": [
1000,
100
],
"tensorPath": "https://gist.githubusercontent.com/ravi07bec/1a24e0ea2867e4f1d30667abb06b4d51/raw/9c77f650b6363b88fe093843f4f352c784d82db3/sample_tensor_artist.tsv"
,
@ravi07bec
ravi07bec / metadata_color.csv
Created October 21, 2020 19:04
We can make this file beautiful and searchable if this error is corrected: No commas found in this CSV file in line 0.
color
acorn
alloy
almond
aloe
american navy
anchor
angel blue
anthracite
antique indigo
@ravi07bec
ravi07bec / sample_tensor_color.tsv
Created October 21, 2020 19:01
We can't make this file beautiful and searchable because it's too large.
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99
-0.008826861 0.14712125 0.14984393 0.03741063 -0.447161 0.750259 0.17495684 0.39537993 -0.19258313 -0.33608186 0.03766776 0.46875164 0.25622755 0.030031884 -0.21934327 0.81438655 -0.30240303 -0.32825795 -0.5412107 0.014231324 0.2349854 1.0813432 -0.12823704 0.25709152 -0.24238282 0.19340871 0.041515462 -0.058305223 0.17574815 0.52108234 0.26135543 -0.5616022 -0.59634197 0.11061073 0.8746614 -0.0008210669 0.25566977 0.3999487 0.13468345 -0.12887232 -0.15199159 -0.06385901 0.10250424 0.33175743 0.10983313 -0.41795734 0.05240363 0.10812743 -0.03821073 -0.11447425 0.009639623 -0.2860793 -0.11930247 0.56726474 -0.33321252 -0.15417482 -0.36149317 -0.11043632 0.18114583 -0.15371099 -0.27607924 -0.36437076 0.015887987 -0.19109431 -0
@ravi07bec
ravi07bec / embeddings.py
Created October 21, 2020 06:21
from datetime import datetime
from gensim.models import Word2Vec
from fse import IndexedList
#Data Inputs
movies=pd.read_csv('ml-latest/movies.csv')
links=pd.read_csv('ml-latest/ratings.csv')
links=links.sample(frac=0.05)