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Financial News Channels Youtube Data EDA

1 Bloomberg

Is a privately held financial, software, data, and media company headquartered in Midtown Manhattan, New York City. It was co-founded by Michael Bloomberg in 1981, with Thomas Secunda, Duncan MacMillan, Charles Zegar,[9] and a 12% ownership investment by Bank of America through their brokerage subsidiary Merrill Lynch.[10]

2 CNBC

is an American basic cable business news channel and website. It provides business news programming on weekdays from 5:00 a.m. to 7:00 p.m., Eastern Time, while broadcasting talk shows, investigative reports, documentaries, infomercials, reality shows, and other programs at all other times.

3 Yahoo Finance

It provides financial news, data and commentary including stock quotes, press releases, financial reports, and original content.

4 The Economist

is a British weekly newspaper printed in magazine format and published digitally. It focuses on current affairs, international business, politics, technology, and culture

5 Kitco News

At Kitco News, we deliver insightful, reliable, comprehensive investment news and analysis. We provide a range of opinions and perspectives allowing our viewers to make informed decisions. Our journalists interview experts, analysts, traders, authors and industry leaders across various sectors, including precious metals, cryptocurrencies, commodities, finance, geopolitics and technology.

# lets import libraries
from googleapiclient.discovery import build
import pandas as pd
import seaborn as sns

1 Bloomberg​ Channel Stats

Function to get Bloomberg channel statistics

api_key = 'AIzaSyB24Kop04L1GlTgRCm1XtQ4KB2a4gaBOwA'
Bloomberg_channel_id = ['UCIALMKvObZNtJ6AmdCLP7Lg' # Bloomberg
     
              ]
youtube = build('youtube','v3',developerKey = api_key)

from googleapiclient.errors import HttpError

def get_channel_stats(youtube, Bloomberg_channel_id):
    all_data = []
    try:
        request = youtube.channels().list(
            part='snippet,contentDetails,statistics',
            id=','.join(Bloomberg_channel_id)
        )
        response = request.execute()

        for item in response.get('items', []):
            snippet = item.get('snippet', {})
            statistics = item.get('statistics', {})

            data = {
                'Channel_name': snippet.get('title', ''),
                'Subscribers': statistics.get('subscriberCount', ''),
                'Views': statistics.get('viewCount', ''),
                'Total_videos': statistics.get('videoCount', '')
            }

            all_data.append(data)

    except HttpError as e:
        print(f"HTTP error occurred: {e}")
        print(f"Request URL: {e.resp.request.url}")
        print(f"Request body: {e.resp.request.body}")

    return all_data

get_channel_stats(youtube,Bloomberg_channel_id)

[{'Channel_name': 'Bloomberg Television',
  'Subscribers': '1790000',
  'Views': '778358870',
  'Total_videos': '61566'}]

channel_statistics = get_channel_stats(youtube, Bloomberg_channel_id)

Bloomberg_channel_data =pd.DataFrame(channel_statistics) 

Bloomberg_channel_data

	Channel_name	Subscribers	Views	Total_videos
0	Bloomberg Television	1790000	778358870	61566

2 CNBC Channel Stats

Function to get CNBC channel statistics

api_key = 'AIzaSyB24Kop04L1GlTgRCm1XtQ4KB2a4gaBOwA'
CNBC_channel_id = ['UCvJJ_dzjViJCoLf5uKUTwoA' # CNBC
     
              ]
youtube = build('youtube','v3',developerKey = api_key)

from googleapiclient.errors import HttpError

def get_channel_stats(youtube, CNBC_channel_id):
    all_data = []
    try:
        request = youtube.channels().list(
            part='snippet,contentDetails,statistics',
            id=','.join(CNBC_channel_id)
        )
        response = request.execute()

        for item in response.get('items', []):
            snippet = item.get('snippet', {})
            statistics = item.get('statistics', {})

            data = {
                'Channel_name': snippet.get('title', ''),
                'Subscribers': statistics.get('subscriberCount', ''),
                'Views': statistics.get('viewCount', ''),
                'Total_videos': statistics.get('videoCount', '')
            }

            all_data.append(data)

    except HttpError as e:
        print(f"HTTP error occurred: {e}")
        print(f"Request URL: {e.resp.request.url}")
        print(f"Request body: {e.resp.request.body}")

    return all_data

get_channel_stats(youtube, CNBC_channel_id)

[{'Channel_name': 'CNBC',
  'Subscribers': '3300000',
  'Views': '1490322437',
  'Total_videos': '15177'}]

channel_statistics = get_channel_stats(youtube, CNBC_channel_id)

CNBC_channel_data =pd.DataFrame(channel_statistics) 

CNBC_channel_data

	Channel_name	Subscribers	Views	Total_videos
0	CNBC	3300000	1490322437	15177

3 Yahoo Finance Channel Stats

Function to get Yahoo Finance channel statistics

api_key = 'AIzaSyB24Kop04L1GlTgRCm1XtQ4KB2a4gaBOwA'
Yahoo_Finance_id = ['UCEAZeUIeJs0IjQiqTCdVSIg' # Yahoo Finance
     
              ]
youtube = build('youtube','v3',developerKey = api_key)

from googleapiclient.errors import HttpError

def get_channel_stats(youtube, Yahoo_Finance_id):
    all_data = []
    try:
        request = youtube.channels().list(
            part='snippet,contentDetails,statistics',
            id=','.join(Yahoo_Finance_id)
        )
        response = request.execute()

        for item in response.get('items', []):
            snippet = item.get('snippet', {})
            statistics = item.get('statistics', {})

            data = {
                'Channel_name': snippet.get('title', ''),
                'Subscribers': statistics.get('subscriberCount', ''),
                'Views': statistics.get('viewCount', ''),
                'Total_videos': statistics.get('videoCount', '')
            }

            all_data.append(data)

    except HttpError as e:
        print(f"HTTP error occurred: {e}")
        print(f"Request URL: {e.resp.request.url}")
        print(f"Request body: {e.resp.request.body}")

    return all_data

get_channel_stats(youtube, Yahoo_Finance_id)

[{'Channel_name': 'Yahoo Finance',
  'Subscribers': '1100000',
  'Views': '405205248',
  'Total_videos': '46980'}]

channel_statistics = get_channel_stats(youtube, Yahoo_Finance_id)

Yahoo_channel_data =pd.DataFrame(channel_statistics) 

Yahoo_channel_data

	Channel_name	Subscribers	Views	Total_videos
0	Yahoo Finance	1100000	405205248	46980

4 The Economist Channel Stats

Function to get The Economist channel statistics

api_key = 'AIzaSyB24Kop04L1GlTgRCm1XtQ4KB2a4gaBOwA'
The_Economist_channel_id = ['UC0p5jTq6Xx_DosDFxVXnWaQ' # The Economist
     
              ]
youtube = build('youtube','v3',developerKey = api_key)

from googleapiclient.errors import HttpError

def get_channel_stats(youtube, The_Economist_channel_id):
    all_data = []
    try:
        request = youtube.channels().list(
            part='snippet,contentDetails,statistics',
            id=','.join(The_Economist_channel_id)
        )
        response = request.execute()

        for item in response.get('items', []):
            snippet = item.get('snippet', {})
            statistics = item.get('statistics', {})

            data = {
                'Channel_name': snippet.get('title', ''),
                'Subscribers': statistics.get('subscriberCount', ''),
                'Views': statistics.get('viewCount', ''),
                'Total_videos': statistics.get('videoCount', '')
            }

            all_data.append(data)

    except HttpError as e:
        print(f"HTTP error occurred: {e}")
        print(f"Request URL: {e.resp.request.url}")
        print(f"Request body: {e.resp.request.body}")

    return all_data

get_channel_stats(youtube, The_Economist_channel_id)

[{'Channel_name': 'The Economist',
  'Subscribers': '3260000',
  'Views': '328815390',
  'Total_videos': '600'}]

channel_statistics = get_channel_stats(youtube, The_Economist_channel_id)

The_Economist_channel_data =pd.DataFrame(channel_statistics) 

The_Economist_channel_data

	Channel_name	Subscribers	Views	Total_videos
0	The Economist	3260000	328815390	600

1 Kitco News Channel Stats

Function to get Kitco News channel statistics

api_key = 'AIzaSyB24Kop04L1GlTgRCm1XtQ4KB2a4gaBOwA'
Kitco_News_channel_id = ['UC9ijza42jVR3T6b8bColgvg' # Kitco News
     
              ]
youtube = build('youtube','v3',developerKey = api_key)

from googleapiclient.errors import HttpError

def get_channel_stats(youtube, Kitco_News_channel_id):
    all_data = []
    try:
        request = youtube.channels().list(
            part='snippet,contentDetails,statistics',
            id=','.join(Kitco_News_channel_id)
        )
        response = request.execute()

        for item in response.get('items', []):
            snippet = item.get('snippet', {})
            statistics = item.get('statistics', {})

            data = {
                'Channel_name': snippet.get('title', ''),
                'Subscribers': statistics.get('subscriberCount', ''),
                'Views': statistics.get('viewCount', ''),
                'Total_videos': statistics.get('videoCount', '')
            }

            all_data.append(data)

    except HttpError as e:
        print(f"HTTP error occurred: {e}")
        print(f"Request URL: {e.resp.request.url}")
        print(f"Request body: {e.resp.request.body}")

    return all_data

get_channel_stats(youtube, Kitco_News_channel_id )

[{'Channel_name': 'Kitco NEWS',
  'Subscribers': '613000',
  'Views': '144857028',
  'Total_videos': '4247'}]

channel_statistics = get_channel_stats(youtube,Kitco_News_channel_id )

Kitco_News_channel_data =pd.DataFrame(channel_statistics) 

Kitco_News_channel_data

	Channel_name	Subscribers	Views	Total_videos
0	The Economist	3260000	328815390	600

# Combine DataFrames using concat
combined_Financial_News_channels_df = pd.concat([
                                        Bloomberg_channel_data ,
                                      CNBC_channel_data,
                                       Yahoo_channel_data , 
                                       The_Economist_channel_data ,
                                       Kitco_News_channel_data,
                                      ], ignore_index=True)

# Display the result
print(combined_Financial_News_channels_df)

           Channel_name Subscribers       Views Total_videos
0  Bloomberg Television     1790000   778358870        61566
1                  CNBC     3300000  1490322437        15177
2         Yahoo Finance     1100000   405205248        46980
3         The Economist     3260000   328815390          600
4         The Economist     3260000   328815390          600

# lets have  a look at the datatypes
combined_Financial_News_channels_df.info()

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 5 entries, 0 to 4
Data columns (total 4 columns):
 #   Column        Non-Null Count  Dtype 
---  ------        --------------  ----- 
 0   Channel_name  5 non-null      object
 1   Subscribers   5 non-null      int64 
 2   Views         5 non-null      int64 
 3   Total_videos  5 non-null      int64 
dtypes: int64(3), object(1)
memory usage: 292.0+ bytes

# lets change the datatypes to perform  visualisations
combined_Financial_News_channels_df['Subscribers'] = pd.to_numeric(combined_Financial_News_channels_df['Subscribers'])
combined_Financial_News_channels_df['Views'] = pd.to_numeric(combined_Financial_News_channels_df['Views'])
combined_Financial_News_channels_df['Total_videos'] = pd.to_numeric(combined_Financial_News_channels_df['Total_videos'])
# letsconirm if the datatypes has changed
combined_Financial_News_channels_df.info()

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 5 entries, 0 to 4
Data columns (total 4 columns):
 #   Column        Non-Null Count  Dtype 
---  ------        --------------  ----- 
 0   Channel_name  5 non-null      object
 1   Subscribers   5 non-null      int64 
 2   Views         5 non-null      int64 
 3   Total_videos  5 non-null      int64 
dtypes: int64(3), object(1)
memory usage: 292.0+ bytes

combined_Financial_News_channels_df

	Channel_name	Subscribers	Views	Total_videos
0	Bloomberg Television	1790000	778358870	61566
1	CNBC	3300000	1490322437	15177
2	Yahoo Finance	1100000	405205248	46980
3	The Economist	3260000	328815390	600
4	The Economist	3260000	328815390	600

import matplotlib.pyplot as plt

# Sort the DataFrame by 'Subscribers' in descending order
combined_Financial_News_channels_df_subscribers_sorted =combined_Financial_News_channels_df.sort_values(by='Subscribers', ascending=False)

# Plotting Subscribers in descending order
fig, axes = plt.subplots(nrows=3, ncols=1, figsize=(10, 15))

axes[0].bar(combined_Financial_News_channels_df_subscribers_sorted['Channel_name'], combined_Financial_News_channels_df_subscribers_sorted['Subscribers'], color='blue')
axes[0].set_title('Subscribers')

# Sort the DataFrame by 'Views' in descending order
combined_Financial_News_channels_df_views_sorted = combined_Financial_News_channels_df.sort_values(by='Views', ascending=False)

# Plotting Views in descending order
axes[1].bar(combined_Financial_News_channels_df_views_sorted['Channel_name'], combined_Financial_News_channels_df_views_sorted['Views'], color='green')
axes[1].set_title('Views')

# Sort the DataFrame by 'Total_videos' in descending order
combined_Financial_News_channels_df_total_videos_sorted = combined_Financial_News_channels_df.sort_values(by='Total_videos', ascending=False)

# Plotting Total Videos in descending order
axes[2].bar(combined_Financial_News_channels_df_total_videos_sorted['Channel_name'], combined_Financial_News_channels_df_total_videos_sorted['Total_videos'], color='orange')
axes[2].set_title('Total Videos')

# Adjust layout for better visibility
plt.tight_layout()

# Show the plot
plt.show()