Input

mydfs= [df1,df2,df3,df4,df5,df6,df7,df8,df9]

My Code

import pandas as pd

df_1 = pd.concat([mydfs[0],mydfs[1],mydfs[2]])

df_m = df_1.merge(mydfs[2])

df_2 = pd.concat([mydfs[3],mydfs[4],mydfs[5]])

df_m1 = df_2.merge(mydfs[5])

df_3 = pd.concat([mydfs[6],mydfs[7],mydfs[8]])

df_m2 = df_3.merge(mydfs[8])

But I want my code dynamic way instead of doing manually, using for loop is it possible? may be in future the list of data frames will increase

CodePudding user response：

You can use a loop with "globals" to iterate through mydfs and define two "kth" variables each round

i = 0
k = 1
while i < len(mydfs):
    globals()["df_{}".format(k)]  = pd.concat([mydfs[i],mydfs[i 1],mydfs[i 2]])
    globals()["df_m{}".format(k)] = globals()["df_{}".format(k)].merge(mydfs[i 2])
    i = i 3
    k = k 1

CodePudding user response：

You can use a dictionary comprehension:

N = 3
out_dfs = {f'df_{i//N 1}': pd.concat(mydfs[i:i N])
           for i in range(0, len(mydfs), N)}

output:

{'df_1': <concatenation result of ['df1', 'df2', 'df3']>,
 'df_2': <concatenation result of ['df4', 'df5', 'df6']>,
 'df_3': <concatenation result of ['df7', 'df8', 'df9']>,
}