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,,,,,