diff --git a/zuoye/__pycache__/datas.cpython-311.pyc b/zuoye/__pycache__/datas.cpython-311.pyc
new file mode 100644
index 0000000000000000000000000000000000000000..14438810bd6e3696ec710ea018f78b6d7a140ad0
Binary files /dev/null and b/zuoye/__pycache__/datas.cpython-311.pyc differ
diff --git a/zuoye/datas.py b/zuoye/datas.py
new file mode 100644
index 0000000000000000000000000000000000000000..ee5d055d08259ada53011bfb3596a82f4774454c
--- /dev/null
+++ b/zuoye/datas.py
@@ -0,0 +1,114 @@
+#预测系统
+#模拟太原和吕梁的房价数据
+#怎样模拟 城市 面积 户型 学区房 预测的维度越多，预测出来的房价更精准
+datas=[
+    {
+        "city":"吕梁",
+        "area":100,
+        "rooms":2,
+        "school":1,
+        "style":1,
+        "price":7600,
+
+    },
+{
+        "city":"吕梁",
+        "area":100,
+        "rooms":2,
+        "school":1,
+        "style":2,
+        "price":7900,
+
+    },
+{
+        "city":"吕梁",
+        "area":145,
+        "rooms":2,
+        "school":1,
+        "style":1,
+        "price":8500,
+
+    },
+{
+        "city":"吕梁",
+        "area":135,
+        "rooms":3,
+        "school":1,
+        "style":1,
+        "price":6300,
+
+    },
+{
+        "city":"吕梁",
+        "area":145,
+        "rooms":3,
+        "school":1,
+        "style":1,
+        "price":6500,
+
+    },
+{
+        "city":"吕梁",
+        "area":140,
+        "rooms":3,
+        "school":1,
+        "style":1,
+        "price":6600,
+
+    },
+    #taiyuan
+{
+        "city":"太原",
+        "area":100,
+        "rooms":2,
+        "school":1,
+        "style":1,
+        "price":10000,
+
+    },
+{
+        "city":"太原",
+        "area":120,
+        "rooms":2,
+        "school":1,
+        "style":1,
+        "price":9800,
+
+    },
+{
+        "city":"太原",
+        "area":100,
+        "rooms":3,
+        "school":1,
+        "style":1,
+        "price":9500,
+
+    },
+{
+        "city":"太原",
+        "area":135,
+        "rooms":3,
+        "school":2,
+        "style":2,
+        "price":9300,
+
+    },
+{
+        "city":"太原",
+        "area":145,
+        "rooms":3,
+        "school":2,
+        "style":2,
+        "price":9500,
+
+    },
+{
+        "city":"太原",
+        "area":140,
+        "rooms":3,
+        "school":2,
+        "style":2,
+        "price":9600,
+
+    },
+]#列表
diff --git a/zuoye/predict.py b/zuoye/predict.py
new file mode 100644
index 0000000000000000000000000000000000000000..eef602ee654eea20428b83efd8b0ba5986202ff4
--- /dev/null
+++ b/zuoye/predict.py
@@ -0,0 +1,8 @@
+#1.安装一个科学计算的框架
+import numpy as np
+a=np.array([[1,2,3],[1,2,3],[1,2,3]])
+b=np.array([1,2,3])
+print(a.dot(b)) #dot:两个矩阵之间的乘法
+print(a)
+print(a.T)   # 矩阵称呼.T:求矩阵的转置
+print(np.linalg.pinv(a))   # np.linalg.pinv(矩阵称呼)：矩阵的逆 (可以排除奇异矩阵）
diff --git a/zuoye/predict1.py b/zuoye/predict1.py
new file mode 100644
index 0000000000000000000000000000000000000000..4da7529a6ff7916c14c7a302715a4620a7e0e25a
--- /dev/null
+++ b/zuoye/predict1.py
@@ -0,0 +1,19 @@
+import numpy as np
+from datas import datas
+X=[]
+Y=[]
+cityMark={"吕梁":1,"太原":2}
+for item in datas:
+    single=[]
+    single.append(cityMark[item["city"]])
+    single.append(item["area"])
+    single.append(item["rooms"])
+    single.append(item["school"])
+    single.append(item["style"])
+    X.append(single)
+    Y.append(item["price"])
+
+X=np.array(X)
+Y=np.array(Y)
+theta=np.linalg.pinv(X.T.dot(X)).dot(X.T).dot(Y)
+print(theta.dot(np.array([2,150,2,1,1])))
\ No newline at end of file