在 python 中自己的结果旁边打印客户编号

print customer number next to the own result in python

我的代码:

import pandas as pd
from sklearn.tree import DecisionTreeClassifier
from sklearn.model_selection import train_test_split

df = pd.read_csv('orderlist.csv', skiprows=1, delimiter=';', encoding="utf8")
df.columns = ["date", "customer_number", "item_code", "quantity"]

df['customer_item'] = df.customer_number + ', ' + df.item_code
df['date'] = pd.to_datetime(df['date'])

df["quantity"] = df["quantity"].astype(int, errors='ignore')

df["week"]=df.date.dt.week
df_grup = df.groupby(by=['week',"customer_item"]).quantity.sum().reset_index()
df_dum = pd.get_dummies(df_grup)

X, y = df_dum, df_dum["quantity"]
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=0)

dtree = DecisionTreeClassifier().fit(X_train, y_train)
predict = dtree.fit(X_train, y_train)
y_pred = dtree.predict(X_test)

pred_quantity = dtree.predict(df_dum)
print("predict quantity:")
print(pred_quantity)

结果:

predict quantity:
[100   5 450 ... 295  22 639]

我需要在自己的结果旁边打印客户编号。

pred_quantity第n项对应df['customer_number']

第n项

因此您可以将 pred_quantity 作为列添加到 df

df['pred_quantity'] = pred_quantity
print(df[['customer_number', 'pred_quantity']])

或使用 zip (docs) 并排打印它们

for number, quantity in zip(df['customer_number'], pred_quantity)
    print(number, quantity)