[python] Get the name of a pandas DataFrame

How do I get the name of a DataFrame and print it as a string?

Example:

boston (var name assigned to a csv file)

import pandas as pd
boston = pd.read_csv('boston.csv')

print('The winner is team A based on the %s table.) % boston

Sometimes df.name doesn't work.

you might get an error message:

'DataFrame' object has no attribute 'name'

try the below function:

def get_df_name(df):
    name =[x for x in globals() if globals()[x] is df][0]
    return name

Here is a sample function: 'df.name = file` : Sixth line in the code below

def df_list(): filename_list = current_stage_files(PATH) df_list = [] for file in filename_list: df = pd.read_csv(PATH+file) df.name = file df_list.append(df) return df_list

You can name the dataframe with the following, and then call the name wherever you like:

import pandas as pd
df = pd.DataFrame( data=np.ones([4,4]) )
df.name = 'Ones'

print df.name
>>>
Ones

Hope that helps.

In many situations, a custom attribute attached to a pd.DataFrame object is not necessary. In addition, note that pandas-object attributes may not serialize. So pickling will lose this data.

Instead, consider creating a dictionary with appropriately named keys and access the dataframe via dfs['some_label'].

df = pd.DataFrame()

dfs = {'some_label': df}

From here what I understand DataFrames are:

DataFrame is a 2-dimensional labeled data structure with columns of potentially different types. You can think of it like a spreadsheet or SQL table, or a dict of Series objects.

And Series are:

Series is a one-dimensional labeled array capable of holding any data type (integers, strings, floating point numbers, Python objects, etc.).

Series have a name attribute which can be accessed like so:

 In [27]: s = pd.Series(np.random.randn(5), name='something')

 In [28]: s
 Out[28]: 
 0    0.541
 1   -1.175
 2    0.129
 3    0.043
 4   -0.429
 Name: something, dtype: float64

 In [29]: s.name
 Out[29]: 'something'

EDIT: Based on OP's comments, I think OP was looking for something like:

 >>> df = pd.DataFrame(...)
 >>> df.name = 'df' # making a custom attribute that DataFrame doesn't intrinsically have
 >>> print(df.name)
 'df'