diff --git a/bottom_function/data_read.py b/bottom_function/data_read.py
new file mode 100644
index 0000000000000000000000000000000000000000..8a8940264bf0ca854a1f60a7f5660fab53093a4b
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+++ b/bottom_function/data_read.py
@@ -0,0 +1,106 @@
+# -*- coding: utf-8 -*-
+# author：Li Mingjie time:2019/1/27
+# Brief: read data
+import pandas as pd
+import bottom_function.m_SQL as qb
+import re
+
+
+def read_data(datatype, starttime, endtime):
+    csv_data = pd.DataFrame()
+    m_data = pd.DataFrame()
+    tablename = "semantic_data_table"
+    db = qb.Schema(host="localhost", user="root", password="560193", mysqlName="semantic_data_schema", port="3306")
+    csv_data = db.getData(tableName=tablename, startTime=starttime, endTime=endtime)
+    if datatype == "control":
+        m_data = csv_data[csv_data['classify'] == 'gree']
+    elif datatype == "application":
+        m_data = csv_data[csv_data['classify'] == 'tencent']
+    elif datatype == "chat":
+        m_data = csv_data[csv_data['domain'] == 'chat']
+    elif datatype == "all":
+        m_data = csv_data
+    elif datatype == "error_control":
+        m_data = db.getData(tableName="control_error_data", startTime=starttime, endTime=endtime)
+    elif datatype == "error_application":
+        m_data = db.getData(tableName="application_error_data", startTime=starttime, endTime=endtime)
+    else:
+        print("The datatype you selected is incorrect. Please re-select it.")
+        return -1
+    return m_data
+
+
+def read_domain_data(datatype, starttime, endtime):
+    csv_data = pd.DataFrame()
+    if datatype == "control":
+        tablename = "control_domain_data"
+        db = qb.Schema(host="localhost", user="root", password="560193", mysqlName="semantic_data_schema", port="3306")
+        csv_data = db.getData(tableName=tablename, startTime=starttime, endTime=endtime)
+
+    elif datatype == "application":
+        tablename = "application_domain_data"
+        db = qb.Schema(host="localhost", user="root", password="560193", mysqlName="semantic_data_schema", port="3306")
+        csv_data = db.getData(tableName=tablename, startTime=starttime, endTime=endtime)
+
+    elif datatype == "all":
+        db = qb.Schema(host="localhost", user="root", password="560193", mysqlName="semantic_data_schema", port="3306")
+        gcsv_data = db.getData(tableName="control_domain_data", startTime=starttime, endTime=endtime)
+        tcsv_data = db.getData(tableName="application_domain_data", startTime=starttime, endTime=endtime)
+        tcsv_data = tcsv_data.drop(columns=['datetime'])
+        csv_data = pd.concat([gcsv_data, tcsv_data], axis=1)
+    return csv_data
+
+
+def read_cost_time_data(datatype, starttime, endtime):
+    csv_data = pd.DataFrame()
+    cost_data = pd.DataFrame()
+    g_data = pd.DataFrame()
+    t_data = pd.DataFrame()
+    gree_dict = {}
+    tencent_dict = {}
+    all_dict = {}
+    time_dict = {}
+    cost_time_dict = {}
+
+    db = qb.Schema(host="localhost", user="root", password="560193", mysqlName="semantic_data_schema", port="3306")
+    csv_data = db.getData(tableName="cost_time_data", startTime=starttime, endTime=endtime)
+    for col in list(csv_data.columns)[1:]:
+        gree_dict.clear()
+        tencent_dict.clear()
+        all_dict.clear()
+        time_dict.clear()
+
+        for row in range(0, len(csv_data)):
+            m_str = str(csv_data.ix[row, col])
+            c = re.sub('[(),\[\] ]', '', m_str)
+            str_list = c.split("'")
+            m_list = list(filter(None, str_list))
+            if datatype == "control":
+                for i in range(0, 6, 2):
+                    if m_list[i] in gree_dict.keys():
+                        gree_dict[m_list[i]] += int(m_list[i + 1])
+                    else:
+                        gree_dict.update({m_list[i]: int(m_list[i + 1])})
+                time_dict = gree_dict.copy()
+
+            elif datatype == "application":
+                for j in range(6, 12, 2):
+                    if m_list[j] in tencent_dict.keys():
+                        tencent_dict[m_list[j]] += int(m_list[j + 1])
+                    else:
+                        tencent_dict.update({m_list[j]: int(m_list[j + 1])})
+                time_dict = tencent_dict.copy()
+
+            else:
+                for m in range(0, 12, 2):
+                    if m_list[m] in all_dict.keys():
+                        all_dict[m_list[m]] += int(m_list[m + 1])
+                    else:
+                        all_dict.update({m_list[m]: int(m_list[m + 1])})
+                time_dict = all_dict.copy()
+        sort_data_list = sorted(time_dict.items(), key=lambda item: item[1], reverse=True)
+        cost_time_dict.update({col: sort_data_list})
+
+    return cost_time_dict
+
+