pip install --upgrade google-api-python-client
Collecting google-api-python-client
Downloading google_api_python_client-2.38.0-py2.py3-none-any.whl (8.2 MB)
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Installing collected packages: httplib2, uritemplate, google-auth-httplib2, google-api-python-client
Successfully installed google-api-python-client-2.38.0 google-auth-httplib2-0.1.0 httplib2-0.20.4 uritemplate-4.1.1
WARNING: You are using pip version 20.1.1; however, version 22.0.3 is available.
You should consider upgrading via the '/usr/local/bin/python -m pip install --upgrade pip' command.
Note: you may need to restart the kernel to use updated packages.
from googleapiclient.discovery import build
import os
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
API_KEY = os.environ['API_KEY']
CHANNEL_ID = 'UCRgseC5dkTgIVzN1nb5iL-g'
youtube = build('youtube' , 'v3' , developerKey = API_KEY )
# Function to get the channels stats
# It will also contain the upload playlist ID we can use to grab videos.
def get_channel_stats(youtube, channel_id):
request = youtube.channels().list(
part="snippet,contentDetails,statistics",
id=channel_id
)
response = request.execute()
return response['items']
# This will get us a list of videos from a playlist.
# Note a page of results has a max value of 50 so we will
# need to loop over our results with a pageToken
def get_video_list(youtube, upload_id):
video_list = []
request = youtube.playlistItems().list(
part="snippet,contentDetails",
playlistId=upload_id,
maxResults=50
)
next_page = True
while next_page:
response = request.execute()
data = response['items']
for video in data:
video_id = video['contentDetails']['videoId']
if video_id not in video_list:
video_list.append(video_id)
# Do we have more pages?
if 'nextPageToken' in response.keys():
next_page = True
request = youtube.playlistItems().list(
part="snippet,contentDetails",
playlistId=upload_id,
pageToken=response['nextPageToken'],
maxResults=50
)
else:
next_page = False
return video_list
# Once we have our video list we can pass it to this function to get details.
# Again we have a max of 50 at a time so we will use a for loop to break up our list.
def get_video_details(youtube, video_list):
stats_list=[]
# Can only get 50 videos at a time.
for i in range(0, len(video_list), 50):
request= youtube.videos().list(
part="snippet,contentDetails,statistics",
id=video_list[i:i+50]
)
data = request.execute()
for video in data['items']:
title=video['snippet']['title']
published=video['snippet']['publishedAt']
description=video['snippet']['tag']
tag_count= len(video['snippet']["localized"])
view_count=video['statistics'].get('viewCount',0)
like_count=video['statistics'].get('likeCount',0)
dislike_count=video['statistics'].get('dislikeCount',0)
comment_count=video['statistics'].get('commentCount',0)
stats_dict=dict(title=title, description=description, published=published, tag_count=tag_count, view_count=view_count, like_count=like_count, dislike_count=dislike_count, comment_count=comment_count)
stats_list.append(stats_dict)
return stats_list
channel_stats = get_channel_stats(youtube, CHANNEL_ID)
print(channel_stats)
[{'kind': 'youtube#channel', 'etag': 'iYmrQhtWMQ9lgxjbeL0F01sa0Mc', 'id': 'UCRgseC5dkTgIVzN1nb5iL-g', 'snippet': {'title': 'Farming By Faith', 'description': '', 'publishedAt': '2017-07-07T18:34:24Z', 'thumbnails': {'default': {'url': 'https://yt3.ggpht.com/ytc/AKedOLSvu8n3NhFn2Gi1GyjUYeio4RRNd25FzDhEqw=s88-c-k-c0x00ffffff-no-rj', 'width': 88, 'height': 88}, 'medium': {'url': 'https://yt3.ggpht.com/ytc/AKedOLSvu8n3NhFn2Gi1GyjUYeio4RRNd25FzDhEqw=s240-c-k-c0x00ffffff-no-rj', 'width': 240, 'height': 240}, 'high': {'url': 'https://yt3.ggpht.com/ytc/AKedOLSvu8n3NhFn2Gi1GyjUYeio4RRNd25FzDhEqw=s800-c-k-c0x00ffffff-no-rj', 'width': 800, 'height': 800}}, 'localized': {'title': 'Farming By Faith', 'description': ''}}, 'contentDetails': {'relatedPlaylists': {'likes': '', 'uploads': 'UURgseC5dkTgIVzN1nb5iL-g'}}, 'statistics': {'viewCount': '1186', 'subscriberCount': '14', 'hiddenSubscriberCount': False, 'videoCount': '21'}}]
upload_id = channel_stats[0]['contentDetails']['relatedPlaylists']['uploads']
upload_id
video_list = get_video_list(youtube, upload_id)
video_data = get_video_details(youtube, video_list)
df=pd.DataFrame(video_data)
df['title_length'] = df['title'].str.len()
df["view_count"] = pd.to_numeric(df["view_count"])
df["like_count"] = pd.to_numeric(df["like_count"])
df["dislike_count"] = pd.to_numeric(df["dislike_count"])
df["comment_count"] = pd.to_numeric(df["comment_count"])
# reaction used later add up likes + dislikes + comments
df["reactions"] = df["like_count"] + df["dislike_count"] + df["comment_count"] + df["comment_count"]
df.to_csv("GMM-Data.csv")
df.head(20)
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This chart is empty
Chart was probably not set up properly in the notebook
# Histogram of tag count.
chart = sns.distplot( a=df["tag_count"], hist=True, kde=False, rug=False )
chart.set(xlabel='Number of Tags Used', ylabel='Occurrences')
/shared-libs/python3.7/py/lib/python3.7/site-packages/seaborn/distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).
warnings.warn(msg, FutureWarning)
chart = sns.distplot( a=df["title_length"], hist=True, kde=False, rug=False )
chart.set(xlabel='Title Length', ylabel='Occurrences')
df_highest_views = df.nlargest(10, 'view_count')
df_highest_views['title'] = df_highest_views['title'].str[:40]
df_highest_views['view_count_millions'] = df_highest_views['view_count'] / 1000
df_highest_views
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sns.set(rc={'figure.figsize':(20,5)})
plot = sns.barplot(x="view_count_millions", y="title", data=df_highest_views, palette="bright")
plot.set(xlabel='1000 of Views', ylabel='')
plot.set_title('Most Viewed Videos')
plt.xlim(20, 32)
# Most Interations ( Like + Dislikes + Comments)
df_highest_reactions = df.nlargest(10, 'reactions')
df_highest_reactions['title'] = df_highest_reactions['title'].str[:40]
df_highest_reactions['reactions'] = df_highest_reactions['reactions'] / 1000
df_highest_reactions
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VISIT --- https://bit.ly/3M2GsXV ---
Make Your Life More Comfortable - Get this amazing smart bracelet with:
Lightweight design
Endurance
Super Clear Display
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sns.set(rc={'figure.figsize':(20,5)})
plot = sns.barplot(y="title", x="reactions", data=df_highest_reactions, palette="bright")
plot.set(xlabel='Thousands of Reactions', ylabel='')
plt.xticks(rotation=45)
plot.set_title('Most Video Reactions')
plt.xlim(300, 700)
df_highest_disliked = df.nlargest(10, 'dislike_count')
df_highest_disliked['title'] = df_highest_disliked['title'].str[:40]
df_highest_disliked['dislike_count'] = df_highest_disliked['dislike_count'] / 1000
df_highest_disliked
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VISIT --- https://bit.ly/3M2GsXV ---
Make Your Life More Comfortable - Get this amazing smart bracelet with:
Lightweight design
Endurance
Super Clear Display
Heart Rate Monitor
With optical heart rate sensor and visual light band technology, accurate heart rate and blood pressure data can be obtained through precise calculation, so that you can precisely control your body function consumption in the process of exercise.
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How Early Adopters Can Get Involved In Creating An Exponentially Scalable Platform For Agriculture.…
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sns.set(rc={'figure.figsize':(20,5)})
plot = sns.barplot(y="title", x="dislike_count", data=df_highest_disliked, palette="bright")
plot.set(xlabel='Thousands of Thumbs Down', ylabel='')
plt.xticks(rotation=45)
plot.set_title('Most Thumbed Down Videos')
plt.xlim(10, 55)