Python Beginner level [closed]

I created a model that can predict the “decision” of a person in a game of RSP(rock, scissors,paper) by looking at the “gender” and “age”.
I have this excel file that consists of 3 columns(gender, age, decision).
So now I want this model to play RSP against a person and make correct decision considering their age and gender.

CAN SOMEONE PLEASE HELP ME??

DATA:

age gender  D
0   20  0   rock
1   18  0   rock
2   17  0   rock
3   16  0   rock
4   15  0   rock
5   14  0   rock
6   25  0   rock
7   30  0   paper
8   31  0   paper
9   32  0   paper
10  33  0   paper
11  34  0   paper
12  14  1   scissors
13  15  1   scissors
14  16  1   scissors
15  17  1   scissors
16  18  1   scissors
17  19  1   scissors
18  20  1   scissors
19  26  1   paper
20  30  1   paper
21  32  1   paper
22  35  1   paper
23  36  1   paper
24  37  1   paper

This is my code and i get error that gender is not defined:

`import pandas as pd
from sklearn.tree import DecisionTreeClassifier
from sklearn.model_selection import train_test_split
from sklearn.metrics import accuracy_score

# Load data from the Excel file
file_path="decision.csv.xlsx"
game_data = pd.read_excel(file_path)

# Separate features (X) and target variable (y)
X = game_data.drop(columns=['D'])
y = game_data['D']

# Split the data into training and testing sets
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.4, random_state=42)

# Initialize the Decision Tree model
model = DecisionTreeClassifier()

# Train the model on the training data
model.fit(X_train, y_train)

# Make predictions on the testing data
predictions = model.predict(X_test)

# Evaluate the model's accuracy
score = accuracy_score(y_test, predictions)
print(f'Model Accuracy: {score:.2%}')

# Function to play rock-paper-scissors against the trained model
def play_rps_against_model(age, gender):
    input_data = pd.DataFrame({'age': [age], 'gender': [gender]})
    
    # Make a prediction using the trained model
    prediction = model.predict(input_data)
    
    return prediction[0]

# User input for age and gender
while True:
    age = input("Enter your age: ")
    gender = input("Enter gender (0 for male, 1 for female): ")
    
    try:
        age = int(age)
        gender = int(gender)
        
        if gender not in [0, 1]:
            print("Please enter '0' for female or '1' for male.")
            continue
        
        break
    except ValueError:
        print("Invalid input. Please enter valid numeric values for age and gender.")

# Get the bot's move based on user's age and gender
bot_move = play_rps_against_model(age, gender)

print(f'The bot played: {bot_move}')

ValueError: The feature names should match those that were passed during fit.
Feature names unseen at fit time:

• gender
  Feature names seen at fit time, yet now missing:
• gender