Manipulasi Data dengan Rapidminer - Seri Perkuliahan Data Analytic & Data Mining #07

[@CimolOk-nz5yj]

🎯 Key Takeaways for quick navigation: 00:00 🤖 *Introduction to Data Manipulation Techniques* - Introduction to basic data manipulation techniques like splitting data, replacing missing values, cutting data, and generating concatenations. 01:48 📊 *Exploring Filtered Data Set* - Examination of a data set with 500,000 records, focusing on Samsung and Apple brand filters. - Discussion on increasing data variety by removing certain filters. 02:41 🧩 *Techniques for Data Splitting and Replacement* - Detailed steps on using the 'split' operator to segregate data. - Introduction of 'replace missing value' technique to handle missing data. 05:41 🔍 *Regular Expression and Data Separation* - Explanation of using regular expressions for data separation. - Emphasis on the importance of correct symbol usage in data manipulation. 07:24 🧬 *Analyzing Results of Data Manipulation* - Analysis of the results post data separation and missing value replacement. - Addressing issues with missing values in data sets. 09:00 🔧 *Advanced Replacement of Missing Data* - In-depth explanation of using 'replace missing value' operator. - Handling specific cases of missing data in the dataset. 11:48 ⚙️ *Fine-tuning Data Output* - Discussion on reordering and adjusting data columns for clarity and analysis. - Emphasis on the flexibility of data manipulation for analysis purposes. 14:41 ✂️ *Utilizing the Cut Operator in Data Manipulation* - Explanation of using the 'cut' operator to modify and shorten data values. - Application of this technique on specific data attributes. 17:33 🧱 *Building Data Columns Using Concatenation* - Introduction to the 'generic concatenate' operator for merging data attributes. - Techniques for combining first and last names in a dataset. 22:18 🔄 *Conclusion and Recap of Data Manipulation Techniques* - Recap of various data manipulation techniques covered in the video. - Encouragement for continued learning and exploration in data analytics and mining. Made with HARPA AI

[@upu1000]

mas ijin bertanya bolehkah?

[@KuliahInformatika]

boleh, silakan :)

[@upu1000]

@@KuliahInformatika kak, bgmn cara menghilangkan tanda kutip 1 baik di awal dan akhir pada setiap cell di rapid miner, karena pada setiap datanya di cll ada tanda kutip 1nya, mohon pencerahannya, terima kasih,,,

[@KuliahInformatika]

Pake operator replace. Nanti di panel parameters, bagian "replace what" diisi dgn tanda kutip 1. Mudah2an membantu :)

[@upu1000]

@@KuliahInformatika jadi tanda kuitip satu di awal data dan tanda kutip 1 diakhir data pada setiap cell, tadi sdah saya coba blm bisa hilang, kakak,,,,

[@upu1000]

alhamdulillah sudah solve mas, terima kaih pencerahannya,,,,,