Concatenate/Append many dataframes in pandas - pandas

Question

I have a list of dataframes df1 to df20 that are being created from a loop and I need to concatenate all of them in one go. These dataframes are dynamic and can be any number between 1 to 20 as per the loop that generates in my code.
So, I was trying to create an empty list first and add these dataframe names to it (in a loop for 1 to 20 as example) and to use this list in pd.concat(df_list) as below:
df_list=[]
for in in range(1,21):
df_list.append(f'df{i}')
pd.concat(df_list)
the above code is creating list of dataframe names but in the form of string with quotes like below and I'm unable to concatenate the dataframes using the pd.concat(df_list) as it's considering all the dataframe names as string elements
print(df_list)
['df1', 'df2', 'df3', 'df4', 'df5', 'df6', 'df7', 'df8', 'df9', 'df10', 'df11', 'df12', 'df13', 'df14', 'df15', 'df16', 'df17', 'df18','df19','df20']
Appreciate if anyone can help me in getting this concatenation of dataframes.
I think if I can add the dataframes names without quotes, like df_list=[df0,df1,df2...] then the pd.concat can work or else please let me know if there is any best alternative to get this done. Thanks!
UPDATE
As per commented suggestions, I've created a simple loop to create multiple dataframes and then I tried to append the "names of these dataframes" to an empty list in this loop itself where these dataframes are getting created. But, the o/p is not what am I expecting.
mylist=[]
for x in range(1,4):
globals()[f"df{i}"]=pd.DataFrame(np.random.randint(99,size=(3,3)),columns=['AA','BB','CC'])
mylist.append(globals()[f"df{i}"])
The above code creates 3 dataframes df1,df2 and df3 and also the empty list is getting appended but with the contents of dataframes as shown below
print(mylist)
[ AA BB CC
0 57 92 50
1 33 47 28
2 82 77 46, AA BB CC
0 18 8 75
1 1 15 52
2 4 69 38, AA BB CC
0 19 24 31
1 24 52 62
2 50 8 63]
But, my desired output is not the contents of the dataframes, but the names of the dataframes themselves like below.
print(mylist)
[df1,df2,df3]
Appreciate if anyone can show me how to get this done. I think there must be some simple way to do this.

Answer 1

That's because you're efectively appending strings to your list. If you have named variables, df1 to df20, you can access them by using locals() (or globals() depending on where your named variables are, and if you are concatenating the dataframes in a function or not). Here is an example,
df1 = 0
df2 = 1
df3 = 2
df_list = []
for i in range(1, 4):
df_list.append(locals()[f'df{i}'])
>>> df_list
[0, 1, 2]
EDIT: I think what you want to do is the following:
import pandas as pd
import numpy as np
mylist = []
for x in range(1, 4):
df = pd.DataFrame(np.random.randint(99, size=(3,3)), columns=['AA','BB','CC'])
mylist.append(df)
dfs = pd.concat(mylist)
Note that printing mylist is never going to tell you something along the lines of mylist = [df1, df2, df3], even if you hardcode that. That will print the entire content of all the variables inside your list. If you don't know how many dataframes you're going to concatenate for some reason, then just implement a while loop that breaks when you want to stop creating dataframes.
Consider another example
# create a list of 100 dataframes (df0 to df99)
mylist = []
for x in range(100):
df = pd.DataFrame(np.random.randint(99,size=(3,3)), columns=['AA','BB','CC'])
mylist.append(df)
concat_range = input("Range of dataframes to concatenate (0-100): ")
i, j = concat_range.split(" ")
dfs = pd.concat(mylist[int(i) : int(j)])
# further operations on dfs
Now, let's say I am the user and I want to concatenate df5 to df32.
>>> Range of dataframes to concatenate (0-100): 5 32
>>> dfs
AA BB CC
0 28 37 36
1 34 18 14
2 39 41 97
0 44 66 76
1 57 16 3
.. .. .. ..
1 43 87 74
2 67 70 73
0 40 60 57
1 23 63 70
2 96 24 31
[81 rows x 3 columns]