|
Обратите внимание, что наш сайт не размещает какие-либо файлы из списка. Вы не можете скачать
эти файлы или скачать torrent-файл.
|
| [TGx]Downloaded from torrentgalaxy.to .txt |
585б |
| 0 |
2.28Кб |
| 001 Data Visualization Concepts.en.srt |
8.34Кб |
| 001 Data Visualization Concepts.mp4 |
94.18Мб |
| 001 Introduction.en.srt |
4.04Кб |
| 001 Introduction.mp4 |
37.39Мб |
| 001 Mount Your Drive.en.srt |
4.58Кб |
| 001 Mount Your Drive.mp4 |
17.51Мб |
| 001 Scrape a Simple Non-Wiki Table.en.srt |
5.20Кб |
| 001 Scrape a Simple Non-Wiki Table.mp4 |
33.77Мб |
| 001 Shall We Start With Soup_.en.srt |
3.65Кб |
| 001 Shall We Start With Soup_.mp4 |
34.34Мб |
| 001 What Are Pandas_.en.srt |
11.64Кб |
| 001 What Are Pandas_.mp4 |
69.66Мб |
| 001 What is Webscraping_.en.srt |
6.61Кб |
| 001 What is Webscraping_.mp4 |
40.55Мб |
| 002 A Ghastly Wiki Table.en.srt |
6.70Кб |
| 002 A Ghastly Wiki Table.mp4 |
53.39Мб |
| 002 Basic Data Cleaning With Pandas.en.srt |
4.66Кб |
| 002 Basic Data Cleaning With Pandas.mp4 |
31.78Мб |
| 002 Data and Code.html |
1.01Кб |
| 002 Explore the IPOs.en.srt |
7.91Кб |
| 002 Explore the IPOs.mp4 |
51.48Мб |
| 002 Lets Rummage Inside a Webpage.en.srt |
7.88Кб |
| 002 Lets Rummage Inside a Webpage.mp4 |
83.05Мб |
| 002 Opening a Jupyter Notebook.en.srt |
2.26Кб |
| 002 Opening a Jupyter Notebook.mp4 |
7.86Мб |
| 002 Simple Webscraping-Parse in an HTML.en.srt |
6.75Кб |
| 002 Simple Webscraping-Parse in an HTML.mp4 |
53.86Мб |
| 003 Accessing Data Within the Drive.en.srt |
3.15Кб |
| 003 Accessing Data Within the Drive.mp4 |
15.99Мб |
| 003 Another Way of Reading in HTML Webpages.en.srt |
8.94Кб |
| 003 Another Way of Reading in HTML Webpages.mp4 |
61.45Мб |
| 003 Cleaning the Scraped Data.en.srt |
4.10Кб |
| 003 Cleaning the Scraped Data.mp4 |
20.81Мб |
| 003 IPO Listings.en.srt |
6.28Кб |
| 003 IPO Listings.mp4 |
50.94Мб |
| 003 Python Installation.en.srt |
6.78Кб |
| 003 Python Installation.mp4 |
39.28Мб |
| 003 Sector Performance.en.srt |
2.62Кб |
| 003 Sector Performance.mp4 |
12.65Мб |
| 003 What is HTML_.en.srt |
10.80Кб |
| 003 What is HTML_.mp4 |
112.72Мб |
| 004 Accessing the Different HTML Components.en.srt |
2.95Кб |
| 004 Accessing the Different HTML Components.mp4 |
23.00Мб |
| 004 Making the IPO Listings Usable.en.srt |
7.05Кб |
| 004 Making the IPO Listings Usable.mp4 |
52.76Мб |
| 004 Quickly Scour The Mumbai Real Estate Trends.en.srt |
3.73Кб |
| 004 Quickly Scour The Mumbai Real Estate Trends.mp4 |
22.03Мб |
| 004 Start With Google Colaboratory Environment.en.srt |
7.84Кб |
| 004 Start With Google Colaboratory Environment.mp4 |
36.72Мб |
| 004 String Manipulation To Get a Neater Table.en.srt |
12.95Кб |
| 004 String Manipulation To Get a Neater Table.mp4 |
87.99Мб |
| 004 Tackling Tables-Part 1.en.srt |
10.19Кб |
| 004 Tackling Tables-Part 1.mp4 |
81.45Мб |
| 004 Upload Data From a Local Drive.en.srt |
5.49Кб |
| 004 Upload Data From a Local Drive.mp4 |
22.33Мб |
| 005 Another Way of Tweaking.en.srt |
2.51Кб |
| 005 Another Way of Tweaking.mp4 |
14.70Мб |
| 005 Google Colabs and GPU.en.srt |
7.06Кб |
| 005 Google Colabs and GPU.mp4 |
27.63Мб |
| 005 Install New Packages.en.srt |
2.87Кб |
| 005 Install New Packages.mp4 |
23.16Мб |
| 005 Some Housekeeping.en.srt |
5.28Кб |
| 005 Some Housekeeping.mp4 |
37.56Мб |
| 005 When We Have More Than 1 Table.en.srt |
4.93Кб |
| 005 When We Have More Than 1 Table.mp4 |
38.26Мб |
| 006 Extract Tables Into Pandas-Part1.en.srt |
4.53Кб |
| 006 Extract Tables Into Pandas-Part1.mp4 |
35.77Мб |
| 006 Google Colab Packages.en.srt |
5.07Кб |
| 006 Google Colab Packages.mp4 |
26.49Мб |
| 006 Hello to Airbnb.en.srt |
4.82Кб |
| 006 Hello to Airbnb.mp4 |
42.83Мб |
| 006 More Data Cleaning-Part1.en.srt |
8.49Кб |
| 006 More Data Cleaning-Part1.mp4 |
80.40Мб |
| 007 Exploring Amazon Bestsellers.en.srt |
6.41Кб |
| 007 Exploring Amazon Bestsellers.mp4 |
71.94Мб |
| 007 Extract Tables Into Pandas-Part2.en.srt |
7.82Кб |
| 007 Extract Tables Into Pandas-Part2.mp4 |
59.69Мб |
| 007 More Data Cleaning-Part2.en.srt |
8.42Кб |
| 007 More Data Cleaning-Part2.mp4 |
70.89Мб |
| 008 A Quicker Way to Extract Tabular Data.en.srt |
2.48Кб |
| 008 A Quicker Way to Extract Tabular Data.mp4 |
15.80Мб |
| 008 Extract Amazon Bestsellers in a Dataframe.en.srt |
6.67Кб |
| 008 Extract Amazon Bestsellers in a Dataframe.mp4 |
49.73Мб |
| 008 Geocoding the London Boroughs.en.srt |
9.17Кб |
| 008 Geocoding the London Boroughs.mp4 |
74.17Мб |
| 009 Exporting Data.en.srt |
4.16Кб |
| 009 Exporting Data.mp4 |
41.64Мб |
| 009 Get Table Names.en.srt |
3.59Кб |
| 009 Get Table Names.mp4 |
19.10Мб |
| 009 Mumbai House Prices.en.srt |
5.96Кб |
| 009 Mumbai House Prices.mp4 |
43.95Мб |
| 010 Fuzzy Strings.en.srt |
4.67Кб |
| 010 Fuzzy Strings.mp4 |
50.34Мб |
| 010 Pandas and HTML Tables.en.srt |
5.27Кб |
| 010 Pandas and HTML Tables.mp4 |
55.39Мб |
| 011 Basic Housekeeping Prior To Fuzzy Joining.en.srt |
11.29Кб |
| 011 Basic Housekeeping Prior To Fuzzy Joining.mp4 |
72.94Мб |
| 012 Let's Get Fuzzy.en.srt |
10.95Кб |
| 012 Let's Get Fuzzy.mp4 |
68.00Мб |
| 013 Merge Datasets Based on Geolocations.en.srt |
14.05Кб |
| 013 Merge Datasets Based on Geolocations.mp4 |
99.67Мб |
| 1 |
302.60Кб |
| 10 |
115.31Кб |
| 11 |
345.89Кб |
| 12 |
509.51Кб |
| 13 |
50.73Кб |
| 14 |
315.85Кб |
| 15 |
109.32Кб |
| 16 |
145.72Кб |
| 17 |
116.37Кб |
| 18 |
245.89Кб |
| 19 |
20.57Кб |
| 2 |
332.19Кб |
| 20 |
60.05Кб |
| 21 |
161.96Кб |
| 22 |
274.88Кб |
| 23 |
52.14Кб |
| 24 |
171.06Кб |
| 25 |
365.08Кб |
| 26 |
463.05Кб |
| 27 |
224.70Кб |
| 28 |
250.33Кб |
| 29 |
448.91Кб |
| 3 |
13.46Кб |
| 30 |
112.11Кб |
| 31 |
291.73Кб |
| 32 |
234.02Кб |
| 33 |
160.25Кб |
| 34 |
237.40Кб |
| 35 |
221.29Кб |
| 36 |
383.56Кб |
| 37 |
6.97Кб |
| 38 |
349.49Кб |
| 39 |
3.88Кб |
| 4 |
459.64Кб |
| 40 |
173.68Кб |
| 41 |
482.48Кб |
| 42 |
192.76Кб |
| 43 |
412.94Кб |
| 44 |
503.19Кб |
| 45 |
12.53Кб |
| 46 |
205.58Кб |
| 47 |
310.11Кб |
| 48 |
355.03Кб |
| 5 |
52.91Кб |
| 6 |
105.86Кб |
| 7 |
341.76Кб |
| 8 |
64.69Кб |
| 9 |
59.12Кб |
| TutsNode.com.txt |
63б |