Q:

Removing stand-alone numbers from string in Python

There are a lot of similar questions, but I have not found a solution for my problem. I have a data frame with the following structure/form:
   col_1
0  BULKA TARTA 500G KAJO 1
1  CUKIER KRYSZTAL 1KG KSC 4
2  KASZA JĘCZMIENNA 4*100G 2 0.92
3  LEWIATAN MAKARON WSTĄŻKA 1 0.89

However, I want to achieve the effect:
   col_1
0  BULKA TARTA 500G KAJO
1  CUKIER KRYSZTAL 1KG KSC
2  KASZA JĘCZMIENNA 4*100G
3  LEWIATAN MAKARON WSTĄŻKA

So I want to remove the independent natural and decimal numbers, but leave the numbers in the string with the letters. 
I tried to use df.col_1.str.isdigit().replace([True, False],[np.nan, df.col_1]) , but it only works on comparing the entire cell whether it is a number or not. 
You have some ideas how to do it? Or maybe it would be good to break the column with spaces and then compare?

A:

We could create a function that tries to convert to float. If it fails we return True (not_float)
import pandas as pd

df = pd.DataFrame({"col_1" : ["BULKA TARTA 500G KAJO 1",
                              "CUKIER KRYSZTAL 1KG KSC 4",
                              "KASZA JĘCZMIENNA 4*100G 2 0.92",
                              "LEWIATAN MAKARON WSTĄŻKA 1 0.89"]})

def is_not_float(string):
    try:
        float(string)
        return False
    except ValueError:  # String is not a number
        return True

df["col_1"] = df["col_1"].apply(lambda x: [i for i in x.split(" ") if is_not_float(i)])

df

Or following the example of my fellow SO:ers. However this would treat 130. as a number.
df["col_1"] = (df["col_1"].apply(
    lambda x: [i for i in x.split(" ") if not i.replace(".","").isnumeric()]))

Returns
                          col_1
0    [BULKA, TARTA, 500G, KAJO]
1  [CUKIER, KRYSZTAL, 1KG, KSC]
2   [KASZA, JĘCZMIENNA, 4*100G]
3  [LEWIATAN, MAKARON, WSTĄŻKA]

