all

.idea/misc.xml

 <?xml version="1.0" encoding="UTF-8"?>
 <project version="4">
-  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.9 (task5)" project-jdk-type="Python SDK" />
+  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.9 (task5 - Copy)" project-jdk-type="Python SDK" />
 </project>
\ No newline at end of file

.idea/modules.xml

@@ -2,7 +2,7 @@
 <project version="4">
   <component name="ProjectModuleManager">
     <modules>
-      <module fileurl="file://$PROJECT_DIR$/.idea/task5.iml" filepath="$PROJECT_DIR$/.idea/task5.iml" />
+      <module fileurl="file://$PROJECT_DIR$/.idea/task5pandas_op.iml" filepath="$PROJECT_DIR$/.idea/task5pandas_op.iml" />
     </modules>
   </component>
 </project>
\ No newline at end of file

.idea/task5.iml → .idea/task5pandas_op.iml

@@ -4,7 +4,7 @@
     <content url="file://$MODULE_DIR$">
       <excludeFolder url="file://$MODULE_DIR$/venv" />
     </content>
-    <orderEntry type="inheritedJdk" />
+    <orderEntry type="jdk" jdkName="Python 3.9 (task5 - Copy)" jdkType="Python SDK" />
     <orderEntry type="sourceFolder" forTests="false" />
   </component>
 </module>
\ No newline at end of file

scripts/core/handlers/change_time_data.py

@@ -9,11 +9,11 @@ def time_change(file):
     file_copy['Timestamp'] = file_copy['Timestamp'].dt.strftime(date_format)
 
     #  for storing the pivoted frame to dictionary
-    dict_cols = {}
+    dict_cols = []
     for i in range(0, len(file_copy.columns)):
-        key_dict = "label" + str(i)
-        val_dict = file_copy.columns[i]
-        dict_cols.update({key_dict: val_dict})
+        key_dict = file_copy.columns[i]
+        val_dict = file_copy.columns[i].lower()
+        dict_cols.append({key_dict: val_dict})
 
     # storing the header and body to json
     head_cols = {"header": dict_cols}

scripts/core/handlers/melted_data_frames.py

@@ -5,14 +5,15 @@ def melt_frame(file):
     file_copy = file
 
     # creating the melted dataframe melted_file
-    melted_file = file_copy.melt(id_vars=['Timestamp'], value_vars=['kWh'])
+    melted_file = file_copy.melt(id_vars=['Timestamp'])
+    print(melted_file)
 
     #  for storing the melted frame to dictionary
-    dict_cols = {}
+    dict_cols = []
     for i in range(0, len(melted_file.columns)):
         key_dict = "label" + str(i)
         val_dict = melted_file.columns[i]
-        dict_cols.update({key_dict: val_dict})
+        dict_cols.append({key_dict: val_dict})
 
     # storing the header and body to json
     head_cols = {"header": dict_cols}

scripts/core/handlers/merge_data_frames.py

@@ -11,13 +11,14 @@ def merge_frame(file):
 
     # creating the merged dataframe merged_file
     merged_file = pd.merge(file_frame1, file_frame2, on='Timestamp')
+    print(merged_file)
 
     #  for storing the merged frame to dictionary
-    dict_cols = {}
+    dict_cols = []
     for i in range(0, len(merged_file.columns)):
         key_dict = "label" + str(i)
         val_dict = merged_file.columns[i]
-        dict_cols.update({key_dict: val_dict})
+        dict_cols.append({key_dict: val_dict})
 
     # storing the header and body to json
     head_cols = {"header": dict_cols}

scripts/core/handlers/pivoted_data_frames.py

@@ -3,18 +3,16 @@
 
 def pivot_frame(file):
     file_copy = file
-
     # pivoting the data
     pivoted_d = file_copy.pivot_table(index='Timestamp', columns=[],
                                       values=file_copy)
-
+    print(pivoted_d)
     #  for storing the pivoted frame to dictionary
-    dict_cols = {}
+    dict_cols = []
     for i in range(0, len(pivoted_d.columns)):
         key_dict = "label"+str(i)
         val_dict = pivoted_d.columns[i]
-        dict_cols.update({key_dict: val_dict})
-
+        dict_cols.append({key_dict: val_dict})
     # storing the header and body to json
     head_cols = {"header": dict_cols}
     body_vals = {"body": pivoted_d.to_dict(orient="records")}

scripts/json_output/data_merge_json.json

 {
-    "header": {
-        "label0": "Timestamp",
-        "label1": "kW",
-        "label2": "kVA"
-    },
+    "header": [
+        {
+            "label0": "Timestamp"
+        },
+        {
+            "label1": "kW"
+        },
+        {
+            "label2": "kVA"
+        }
+    ],
     "body": [
         {
             "Timestamp": "01-12-19 00-00-21",

scripts/json_output/data_pivot_json.json

 {
-    "header": {
-        "label0": "current",
-        "label1": "kVA",
-        "label2": "kVAh",
-        "label3": "kW",
-        "label4": "kWh"
-    },
+    "header": [
+        {
+            "label0": "current"
+        },
+        {
+            "label1": "kVA"
+        },
+        {
+            "label2": "kVAh"
+        },
+        {
+            "label3": "kW"
+        },
+        {
+            "label4": "kWh"
+        }
+    ],
     "body": [
         {
             "current": 281.58292388916016,

scripts/json_output/data_time_json.json

 {
-    "header": {
-        "label0": "Timestamp",
-        "label1": "kWh",
-        "label2": "kVAh",
-        "label3": "kW",
-        "label4": "kVA",
-        "label5": "current"
-    },
+    "header": [
+        {
+            "Timestamp": "timestamp"
+        },
+        {
+            "kWh": "kwh"
+        },
+        {
+            "kVAh": "kvah"
+        },
+        {
+            "kW": "kw"
+        },
+        {
+            "kVA": "kva"
+        },
+        {
+            "current": "current"
+        }
+    ],
     "body": [
         {
             "Timestamp": "01-12-19 00-00-21",

scripts/services/access_operations.py

@@ -18,14 +18,14 @@ def access_op():
 
         print("Pivoting the dataframe")
         dict_data_pivoted, pivot_change = json_pandas.pivot_data(file_concat)
-        json_pandas.create_json(path_pivot, pivot_change)
+        json_pandas.create_json(path_pivot, dict_data_pivoted)
 
         print("Melting the dataframe")
-        melt_change = json_pandas.melt_data(dict_data_pivoted)
+        melt_change = json_pandas.melt_data(file_concat)
         json_pandas.create_json(path_melt, melt_change)
 
         print("Merging the dataframe")
-        merge_change = json_pandas.merge_data(dict_data_pivoted)
+        merge_change = json_pandas.merge_data(file_concat)
         json_pandas.create_json(path_merge, merge_change)
 
     except Exception as e: