Python Tutorial: Concatenation

Key Takeaways

in this video you'll learn how to join data with concatenation you may recognize the term concatenate from the concatenate formula used in spreadsheets to combine text cells the concept in pandas is the same and when it's applied to data frames it's like copying and pasting in a spreadsheet or like gluing two pieces of wood together face to face in pandas we use the pandas concat function to concatenate data frames the function allows us to join two or more data frames along either rows or columns concatenate along rows is very useful when working with split data for instance reports are often produced annually with each year saved to a separate tab or file you can vertically stack one or more data frames like these using pandas concat the function will return a single data frame with data ordered by the order of the data frame names you supply such as DF 1 DF 2 and so on basic concatenation works best when each input data frame has separate values for the index such as game key in this example that way the resulting frame will still have an index of unique values also it's worth noting that the concat function includes all rows by default in other words it creates an outer join sometimes the input data frames have generic indexes that overlap like the row numbers in a spreadsheet this case often occurs when batch loading data into data frames without specifying a named index not to worry concatenate Uralla ignore index you can set its value to true and let pandas generate a new uniquely numbered index for the concatenated data frame you can also use concat when combining complementary data here you'll want to concatenate across columns which is like pasting tables side by side you'll need to tell pandas to join by column pandas refers to moving down rows as access equals 0 and across columns as XS equals 1 by specifying axis equals 1 in the concat statement we override the default behavior and join the columns it's worth noting that all columns from the data frames are included by default you may need to drop or rename columns before continuing it's now time to concatenate your knowledge and practice on some day