pandas - Python: Merging many dataframes in most efficient way possible -


right have many different statistics names attached in separate dataframes. in order merge have keep rewriting new dataframe? there more efficient way this?

does pd.merge make easier if names of columns same when merging?

do have recursively write 

pd.merge(left=something, right=somethingelse, left_on='name', right_on='site')

you can first creating list of dataframes , rsult using reduce function

# create data columns = ['v1','v2','v3'] df1 = pd.dataframe(np.random.randint(10, size=(3,3)),columns=columns) df2 = pd.dataframe(np.random.randint(10, size=(3,3)),columns=columns) df3 = pd.dataframe(np.random.randint(10, size=(3,3)),columns=columns)  dfs = [df1,df2,df3] # store in 1 list df_merge = reduce(lambda  left,right: pd.merge(left,right,on=['v1'], how='outer'), dfs)

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