Data Analysis Online Course | Data Analytics Training in Hyderabad

1. Data Combing Techniques Data combining techniques in data analytics involve merging, aggregating, or joining multiple datasets to gain insights and make informed decisions. These techniques are commonly used to consolidate information from various sources. - Data Analytics Online Training Here are some common data combining techniques: 1. Concatenation: This technique is used to combine datasets along a particular axis, typically rows or columns. It is common in cases where the datasets have the same structure. For example, you can concatenate two dataframes in pandas in Python using the `concat` function. 2. Merging and Joining: When dealing with relational data, you can use SQL- style merging and joining operations to combine datasets based on common columns or keys. Common SQL join types include INNER JOIN, LEFT JOIN, RIGHT JOIN, and FULL OUTER JOIN. - Data Analytics Course in Hyderabad 3. Appending: Appending is similar to concatenation but is used when you want to add data from one dataset to another as new rows. This is common in time-series data, where you want to add new data points to an existing dataset. 4. Union: A union operation combines two or more datasets while removing duplicate rows. This is commonly used when dealing with data that has overlapping records.

2. 5. Joining on Multiple Keys: In some cases, you may need to combine datasets by matching on multiple columns or keys, creating more complex merge operations. - Data Analysis Online Training Course 6. Aggregation: You can combine data by grouping it and then applying aggregation functions (e.g., sum, average, count) to calculate summary statistics for each group. This is often used when you have data in a detailed transactional form, and you want to summarize it. 7. Stacking and Unstacking: In hierarchical or multi-index data, you can stack or unstack the data to reorganize it for analysis. 8. Pivoting: Pivoting involves rotating data from a long format to a wide format or vice versa. It is useful for reshaping data for specific analysis or visualization requirements. - Data Analytics Online Training Institute The choice of data combining technique depends on the nature of the data, the specific problem you're trying to solve, and the tools and technologies you are using. It's essential to understand the structure of your data and the relationships between datasets to determine the most appropriate method for combining them. Visualpath is the Leading and Best Institute for learning Data Analytics Course in Hyderabad, Hyderabad. We provide Data Analytics Online Training, you will get the best course at an affordable cost. Attend Free Demo Call on - +91-9989971070. Visit : https://www.visualpath.in/data-analytics- online-training.html