The Pandas function below takes a list of dataframes and concatenates them into. This basic flavor of
concat()joins the dataframes vertically. In other words, the rows of one dataframe gets added on to the previous one.
df = pd.concat([df1,df2,df3])
Or if you want, you can store the list of dataframes into a variable first and then call the concat function. Like so:
# we must import pandas first # put it in the beginning of your file import pandas as pd frames = [df1, df2, df3, df4, df5] df = pd.concat(frames)
On the other hand, if I want to join the dataframes horizontally, then I can use
For example, in the code below, we are merging df1 with df2 using ‘column_name’ as the common column. This is the column from which to base the merge. If there are any other identical columns that exist between the two dataframes, the suffixes are then appended to the each of the column names accordingly.
This particular flavor of
merge() joins the dataframes horizontally. In the words, the columns of the dataframes gets added together to make one big mamma jamma of a dataframe;
df_merged = df1.merge(df2, left_on='column_name', right_on='column_name', suffixes=('_left', '_right'))