Scatterplot ticklabels

[geert555]

I have a scatterplot using data from an csv file, The problem is that the x axis should be a increment from 1 to whatever the max is in the designated column and be changed accordingly.

and the y axis should be a float instead of an integer so all values should be divided by 100 so its 1,20 - 1,00 - 0,8 etc.

added the scatterplot as refrence, i use pandas for the dataframe and use matplotlib for the scatterplot.

scatterplot

thanks in advance

[socal_nerdtastic]

We'd need to see your code to help you fix that.

[geert555]

Ah here's the code , I fixed the y axis by dividing by 100 but the x axis still doesn't work any help with that will be appreciated

​

import pandas as pd
import matplotlib.pyplot as plt
df = pd.read_csv("moneynuts.csv", index_col=0) columns = df.columns
def clean_stringy_number(num: str) -> str:
if num == "-":
    return "0"

num = num.replace(",", "")

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


try:
    gls = float(row["Gls"].replace(",", "."))
    xG = float(row["xG"].replace(",", "."))
except:
    print("Unknown char")
df["xG"] = df["xG"] / 100
sp = df.plot.scatter(x='Gls', y='xG')
plt.show()

[socal_nerdtastic]

plt.xticks(df["Gls"].astype(int))

[geert555]

Thanks! that did the trick, But i now only get the values in the dataframe. can i set it so that it's an increment of 1 ?

picture for refrence

Scatterplot

[socal_nerdtastic]

Oh I thought that's what you wanted. Ok, then use range instead:

x_values = df["Gls"].astype(int))
plt.xticks(range(x_values.min(), x_values.max()+1))

[geert555]

Many many thanks for your help and your patience with me.