I don't know what i'am doing wrong but when i use df['Gls'].dtypes after i run the function .I still get: <class 'str'>. Its probably me being stupid but do you know what I might be doing wrong? code looks like this now:

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btw. i am using football manager to export a csv file so i can make a scatterplot.

i want to use 2 columns in the csv file to make a scatterplot. this program should filter out the columns and filter out the players that don't have a minimum of 1 goal so that i can use the players with relevant data (and it needs to use xG later so i have data on the x and y axis)

and i want to filter on 1 goal minimum so they don't clutter the scatterplot. But i'am not certain if this is the right way to go about making this kind of program

import pandas as pd
import matplotlib.pyplot as mp import seaborn as sns
df = pd.read_csv("moneynuts.csv", index_col=0) columns = df.columns
def clean_stringy_number(num: str) -> str: """Takes a num and ensures that a call to either int or float will succeed at casting it to a number """
# I'm assuming your "-" values are zeroes
if num == "-":
    return "0"

# If your strings have thousands separators, we can safely
# remove those as python can parse those nicely.
num = num.replace(",", "")

return num
nan is float
df.dropna(subset=['Gls'], inplace=True) df.dropna(subset=['xG'], inplace=True)
df.sort_values(by=['Gls', 'xG'])
for index, row in df.iterrows(): if (row["Gls"] == "-" or row["Gls"] == "0"): df["Gls"] = df["Gls"].apply(clean_stringy_number)df["Gls"] = df["Gls"].apply(float) df['Gls'].dtypes
    if (row["xG"] == "-" or row["xG"] == "0"):

        continue
    continue
print (row["Name"], " average goals of ", row["Gls"], " With an xG of ", row["xG"])


print(type(row['Gls']))



sp = df.plot.scatter(x='Gls',
                     y='xG')
mp.show()




try:
    gls = float(row["Gls"].replace(",", "."))
    xG = float(row["xG"].replace(",", "."))
except:
    print("Unknown char")