How to create a list of non-empty dataframes names? - python-3.x

Question

I have created a list of dataframe and want to run a loop through the list to run some manipulation on some of those dataframes. Note that although this is a list I have manually created, but this dataframes exist in my code.
df_list = [df_1, df_2, df_3, df_4, df_5, ...]
list_df_matching = []
list_non_matching = []
Most of these dataframes are blank. But 2 of them will have some records in them. I want to find the name of those dataframes and create a new list - list_non_matching
for df_name in df_list:
q = df_name.count()
if q > 0:
list_non_matching.append(df_name)
else:
list_df_matching.append(df_name)
My goal is to get a list of dataframe names like [df_4, df_10], but I am getting the following:
[DataFrame[id: string, nbr: string, name: string, code1: string, code2: string],
DataFrame[id: string, nbr: string, name: string, code3: string, code4: string]]
Is the list approach incorrect? Is there a better way of doing it?

Answer 1

Here is an example to illustrate one way to do it with the help of empty property and Python built-in function globals:
import pandas as pd
df1 = pd.DataFrame()
df2 = pd.DataFrame({"col1": [2, 4], "col2": [5, 9]})
df3 = pd.DataFrame(columns = ["col1", "col2"])
df4 = pd.DataFrame({"col1": [3, 8], "col2": [2, 0]})
df5 = pd.DataFrame({"col1": [], "col2": []})
df_list = [df1, df2, df3, df4, df5]
list_non_matching = [
name
for df in df_list
for name in globals()
if not df.empty and globals()[name] is df
]
print(list_non_matching)
# Output
['df2', 'df4']