Combining Data with Pandas Python For Data Processing

Combining Data with Pandas Python For Data Processing

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Pandas is an open source Python library that provides high-performance data analysis and manipulation tools using its powerful data structures. The name Pandas comes from the word Panel Data which means an Econometrics from Multidimensional data. In 2008, Wes McKinney, a developer started developing pandas when he needed a flexible and high-performance tool for data analysis. Prior to Pandas, Python was mostly used for munging and data preparation.

By using Pandas, we can complete five common steps in data processing and analysis, from loading data, data preparation, manipulating, modeling, and analyzing data. Python with Pandas is used in various fields including academic and commercial fields including finance, economics, Statistics, analytics, and many others.

One of the functions of Pandas Python is to combine several data frames into one dataframe to make the data frame larger by various methods. In many cases, data analysts often use multiple methods to combine data with Pandas Python. Curious what these methods are? Let’s see together!

  1. The appned() method The append() method can be used on data frames or series that are intended to add rows only. If SQL has 2 or more tables then it can be vertically combined with Union. So SQL Union is equivalent to the .append() method in Pandas.

  2. The concat() method The .concat() method can be used on data frames intended for concatenation either row-wise or column-wise. In this method, in the following example, we will occupy the position of the two dataframes below and combine them with concat.

  3. Merge() method The .merge() method is used to combine Series or Data Frames that look similar to the join syntax in SQL, specify left and right tables, join keys and how to join (left, right, inner, full outer). This method can be used for single index or multi-index data frames. In this article we will try to combine data frames with a single index.

  4. The join() method The .join() method is used in the data frame to join the two data sets with the index set in both tables as the join key. Without index, this will not work. This method has several types such as right, left, inder, outer, and so on.