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Real Estate Channels Youtube Data EDA

1 BiggerPockets

offers content that covers every aspect of real estate investing from analyzing deals, how to find & finance properties, tips & advice

2 Grant Cardone.

Having made a name for himself as a major real estate YouTuber,

3 Phil Pustejovsky

nique approach to teaching real estate investing has helped his mentees achieve financial success

4 Graham Stephan

began his career as a real estate agent at the age of 18 and became a billionaire by the age of 26. His videos are based on his own early

5 Loida Velasquez

is a real estate hustler, fitness enthusiast, spontaneous adventurer. Loida's channel will provide you with real estate tips/advice on the daily .

1 BiggerPockets Channel Stats

Function to get BiggerPockets channel statistics

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

api_key = 'AIzaSyB24Kop04L1GlTgRCm1XtQ4KB2a4gaBOwA'
BiggerPockets_channel_id = ['UCVWDbXqQ8cupuVpotWNt2eg' # BiggerPockets
                           ]
              
youtube = build('youtube','v3',developerKey = api_key)

from googleapiclient.errors import HttpError

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

[{'Channel_name': 'BiggerPockets',
  'Subscribers': '1160000',
  'Views': '104779284',
  'Total_videos': '3092'}]

channel_statistics = get_channel_stats(youtube, BiggerPockets_channel_id)

BiggerPockets_channel_data =pd.DataFrame(channel_statistics) 

BiggerPockets_channel_data

	Channel_name	Subscribers	Views	Total_videos
0	BiggerPockets	1160000	104779284	3092

2 Grant Cardone Channel Stats

api_key = 'AIzaSyB24Kop04L1GlTgRCm1XtQ4KB2a4gaBOwA'
Grant_Cardone_channel_id = ['UCdlNK1xcy-Sn8liq7feNxWw' # Grant Cardone
     
              ]
youtube = build('youtube','v3',developerKey = api_key)

from googleapiclient.errors import HttpError

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

[{'Channel_name': 'Grant Cardone',
  'Subscribers': '2510000',
  'Views': '522294867',
  'Total_videos': '5944'}]

channel_statistics = get_channel_stats(youtube, Grant_Cardone_channel_id)

Grant_Cardone_channel_data =pd.DataFrame(channel_statistics)

Grant_Cardone_channel_data

	Channel_name	Subscribers	Views	Total_videos
0	Grant Cardone	2510000	522294867	5944

3 Phil Pustejovsky Youtube Channel

Function to get Phil Pustejovsky channel statistics

api_key = 'AIzaSyB24Kop04L1GlTgRCm1XtQ4KB2a4gaBOwA'
Phil_Pustejovsky_channel_id = ['UC0u4GWBzgYQxM_Rg8npQchg' # Phil Pustejovsky
     
              ]
youtube = build('youtube','v3',developerKey = api_key)

from googleapiclient.errors import HttpError

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

[{'Channel_name': 'Phil Pustejovsky',
  'Subscribers': '330000',
  'Views': '118822902',
  'Total_videos': '286'}]

channel_statistics = get_channel_stats(youtube, Phil_Pustejovsky_channel_id)

Phil_Pustejovsky_channel_data =pd.DataFrame(channel_statistics) 

Phil_Pustejovsky_channel_data

	Channel_name	Subscribers	Views	Total_videos
0	Phil Pustejovsky	330000	118822902	286

4 Graham Stephan Youtube Channel Stats

Function to get Graham Stephan channel statistics

api_key = 'AIzaSyB24Kop04L1GlTgRCm1XtQ4KB2a4gaBOwA'
Graham_Stephan_channel_id = ['UCV6KDgJskWaEckne5aPA0aQ' # Graham Stephan
     
              ]
youtube = build('youtube','v3',developerKey = api_key)

from googleapiclient.errors import HttpError

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

[{'Channel_name': 'Graham Stephan',
  'Subscribers': '4610000',
  'Views': '818870610',
  'Total_videos': '984'}]

channel_statistics = get_channel_stats(youtube, Graham_Stephan_channel_id)

Graham_Stephan_channel_data =pd.DataFrame(channel_statistics) 

Graham_Stephan_channel_data

	Channel_name	Subscribers	Views	Total_videos
0	Graham Stephan	4610000	818870610	984

5 Loida Velasquez Youtube Channel

Function to get Loida Velasquez channel statistics

api_key = 'AIzaSyB24Kop04L1GlTgRCm1XtQ4KB2a4gaBOwA'
Loida_Velasquez_channel_id = ['UCpVj89CY-1kVucDpMmVFb3w' # Loida Velasquez
     
              ]
youtube = build('youtube','v3',developerKey = api_key)

from googleapiclient.errors import HttpError

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

[{'Channel_name': 'Loida Velasquez',
  'Subscribers': '91300',
  'Views': '5484625',
  'Total_videos': '400'}]

channel_statistics = get_channel_stats(youtube, Loida_Velasquez_channel_id)

Loida_Velasquez_channel_data =pd.DataFrame(channel_statistics) 

Loida_Velasquez_channel_data

	Channel_name	Subscribers	Views	Total_videos
0	Loida Velasquez	91300	5484625	400

# Combine DataFrames using concat
combined_real_estate_channels_df = pd.concat([
                                        BiggerPockets_channel_data ,
                                      Grant_Cardone_channel_data,
                                       Phil_Pustejovsky_channel_data , 
                                       Graham_Stephan_channel_data ,
                                       Loida_Velasquez_channel_data,
                                      
                                      
                                      ], ignore_index=True)

# Display the result
print(combined_real_estate_channels_df)

       Channel_name Subscribers      Views Total_videos
0     BiggerPockets     1160000  104779284         3092
1     Grant Cardone     2510000  522294867         5944
2  Phil Pustejovsky      330000  118822902          286
3    Graham Stephan     4610000  818870610          984
4   Loida Velasquez       91300    5484625          400

# lets have  a look at the datatypes
combined_real_estate_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      object
 2   Views         5 non-null      object
 3   Total_videos  5 non-null      object
dtypes: object(4)
memory usage: 292.0+ bytes

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

	Channel_name	Subscribers	Views	Total_videos
0	BiggerPockets	1160000	104779284	3092
1	Grant Cardone	2510000	522294867	5944
2	Phil Pustejovsky	330000	118822902	286
3	Graham Stephan	4610000	818870610	984
4	Loida Velasquez	91300	5484625	400

import matplotlib.pyplot as plt

# Sort the DataFrame by 'Subscribers' in descending order
combined_real_estate_channels_df_subscribers_sorted = combined_real_estate_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_real_estate_channels_df_subscribers_sorted['Channel_name'], combined_real_estate_channels_df_subscribers_sorted['Subscribers'], color='blue')
axes[0].set_title('Subscribers')

# Sort the DataFrame by 'Views' in descendcombined_real_estate_channels_dfing order
combined_real_estate_channels_df_views_sorted = combined_real_estate_channels_df.sort_values(by='Views', ascending=False)

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

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

# Plotting Total Videos in descending order
axes[2].bar(combined_real_estate_channels_df_total_videos_sorted['Channel_name'], combined_real_estate_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()