Pandas array of dataframes

import datetime as dt 
import numpy as np
import pandas as pd

dates_list = [dt.datetime(2015,11,i+1) for i in range(3)]
month_day_list = [d.strftime("%m%d") for d in dates_list]

dataframe_collection = {} # dictionary to store dataframes - generally better than an array

for month_day in month_day_list:	# for each key
  	# Create/ assign your new data:
    new_data = np.random.rand(3,3)
    # Store the new data in the dictionary:
    dataframe_collection[month_day] = pd.DataFrame(new_data, columns=["one", "two", "three"])

# Neat printing code:
for key in dataframe_collection.keys():
    print("\n" +"="*40)
    print(key)
    print("-"*40)
    print(dataframe_collection[key])
    
#The code above prints out the following result:

========================================
1102
----------------------------------------
        one       two     three
0  0.896120  0.742575  0.394026
1  0.414110  0.511570  0.268268
2  0.132031  0.142552  0.074510

========================================
1103
----------------------------------------
        one       two     three
0  0.558303  0.259172  0.373240
1  0.726139  0.283530  0.378284
2  0.776430  0.243089  0.283144

========================================
1101
----------------------------------------
        one       two     three
0  0.849145  0.198028  0.067342
1  0.620820  0.115759  0.809420
2  0.997878  0.884883  0.104158

Source: stackoverflow.com

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