Pandas Get a List Of All Data Frames loaded into memory

You could list all dataframes with the following:

import pandas as pd

# create dummy dataframes
df1 = pd.DataFrame({'Col1' : list(range(100))})
df2 = pd.DataFrame({'Col1' : list(range(100))})

# check whether all variables in scope are pandas dataframe. 
# Dir() will return a list of string representations of the variables. 
# Simply evaluate and test whether they are pandas dataframes
alldfs = [var for var in dir() if isinstance(eval(var), pd.core.frame.DataFrame)]

print(alldfs) # df1, df2

building on previous answers ... this returns a list

import pandas as pd 
%who_ls DataFrame 

however, if you try to run a script it doesn't work

thus

import pandas as pd
sheets=[]    
for var in dir():
    if isinstance(locals()[var], pd.core.frame.DataFrame)  and var[0]!='_':
        sheets.append(var)

since some DataFrames will have a copy for internal use only and those start with '_'

I personally think this approach is much better (if in ipython).

import pandas as pd
%whos DataFrame