Using pandas in python to convert file to shapefile with XYZ columns

Question

I have the following python code to read in an .xyz, .txt or .csv extension file and convert it to a shapefile with the headers as X, Y and Z

import pandas as pd
import os
import geopandas as gpd
from shapely.geometry import Point #convert to 3D GeoPandas GeoDataFrame


input_file = "C:/test/input_xyz.xyz"
file_extension = os.path.splitext(input_file)[-1].lower()

if file_extension == ".xyz":
    df  = pd.read_table(input_file, skiprows=2, sep=r'\,|\t', engine='python', names=['x', 'y', 'z'])
    df.columns = ["x", "y", "z"]

elif file_extension == ".txt" or ".csv":
    df = pd.read_csv(input_file, sep='\,|\t')
    df.columns = ["x", "y", "z"]
    

gdf = gpd.GeoDataFrame(df, geometry=df.apply(lambda row: Point(row.x,row.y,row.z), axis=1))

gdf.to_file("C:/test/output_shp.shp")
print("Shapefile Created!")

However, I seem to be struggling with the X, Y, Z headers throwing the conversion of for each of the file types.

For example: The above .xyz file is in this format

625372.73  234629.36  10.50
625373.35  234630.42  10.35
625374.47  234627.45  10.79
625374.44  234628.46  10.59
625374.45  234629.48  10.44

but if I run my code I get the error TypeError: must be real number, not str

Similarly, one of my CSVs is the format below:

X   Y   Z   date
310746.25   681561.75   -8.82   26/02/2022
310745.75   681561.75   -8.85   26/02/2022
310745.25   681561.75   -8.74   26/02/2022

and when I run my code I get the error ValueError: Length mismatch: Expected axis has 4 elements, new values have 3 elements

I need a way to run my code so that it recognises the file types and adds in x y z as the column headers regardless of the current headers/no. of columns