How to correct the graph - urgent

May I know how to correct my graph as refer to attached image file -



from sklearn import datasets
#load data
iris=datasets.load_iris()
X=iris.data[:,[2,3]]
y=iris.target
from sklearn.model_selection import train_test_split
X_train, X_test,y_train, y_test=train_test_split(X,y,test_size=0.3, random_state=0,stratify=y)
#feature scaling
from sklearn.preprocessing import StandardScaler
sc=StandardScaler()
sc.fit(X_train)
X_train_std=sc.transform(X_train)
X_test_std=sc.transform(X_test)
#Logistic regression
from sklearn.linear_model import LogisticRegression
from sklearn.metrics import accuracy_score
C1=[]
A=[]
C1=[0.001,0.01,0.1,1,10,100,1000]
for i in range(len(C1)):
    lr=LogisticRegression(C=C1[i], random_state=0)
    lr.fit(X_train_std,y_train)
    y_pred=lr.predict(X_test_std)
    A.append(accuracy_score(y_test,y_pred))

#draw figure
import matplotlib.pyplot as plt
plt.plot(C1,A)
plt.gca().set_xscale('log')
plt.title('Logistic Regression')
plt.xlabel('C')
plt.ylabel('Accuracy')
plt.show()

Please see the picture from attached file

Please tell me how to modify the coding so that get the same picture as refer to the attached image file