title added in plots

utils.py

@@ -7,8 +7,8 @@ matplotlib.use('Agg')
 import matplotlib.pyplot as plt
 
 dict_summary={"top3":[],"bottom3":[]}
-fig_size_w, fig_size_h = 8, 6
-fig_size_tr_w, fig_size_tr_h = 8,6
+fig_size_ds_w, fig_size_ds_h = 8, 6
+fig_size_tr_w, fig_size_tr_h = 8, 6
 
 def read_all_csv(path='./rawdata_csv/', extension='csv'):
     result = glob.glob(path+'SRC_R*.{}'.format(extension))
@@ -38,8 +38,9 @@ def statewise_distribution(output_filename, input_df, year, ylabel, main_dimensi
     df_filtered = df_filtered[['Year','State_Name','total','total_by_population']]
     df_sum = df_filtered.groupby(['State_Name','Year'],as_index = False).sum().sort_values("total_by_population",ascending=False)
     
-    fig = plt.figure(figsize=(fig_size_w,fig_size_h))
-    plt.xticks(rotation=90, ha="right")
+    fig = plt.figure(figsize=(fig_size_ds_w,fig_size_ds_h))
+    plt.title(label='KPI: '+ylabel, loc="right", fontsize=15, fontstyle='italic')
+    plt.xticks(rotation=90, ha="right", fontsize=8)
     plt.bar(df_sum['State_Name'],df_sum['total_by_population'], align='center')
     # plt.ylabel('Enrollements/Population')
     plt.ylabel(ylabel)
@@ -68,6 +69,7 @@ def total_enrolment_by_category(output_filename, input_df, main_dimension, state
         plt.plot(df_madr['Year'],df_madr['total'],color='b', label='Madrasas')
     
     plt.legend()
+    plt.title(label='KPI: '+ylabel, loc="right", fontsize=15, fontstyle='italic')
     plt.xticks(np.arange(min_year, max_year+1, 1.0))
     plt.ylabel(ylabel)
     plt.xlabel('Year')
@@ -106,6 +108,7 @@ def total_teachers_by_main_dimension(output_filename, input_df, main_dimension,
         plt.plot(df_phd['Year'],df_phd['total'],color='m', label='M.Phil / Ph.D')
 
     plt.legend()
+    plt.title(label='KPI: '+"Number of Teachers", loc="right", fontsize=15, fontstyle='italic')
     plt.xticks(np.arange(min_year, max_year+1, 1.0))
     plt.ylabel('Number of Teachers')
     plt.xlabel('Year')
@@ -129,6 +132,7 @@ def total_classrooms_by_trend(output_filename, input_df, state_code):
     plt.plot(df_major_repair['Year'],df_major_repair['total'],color='b', label='Need Major Repair')
 
     plt.legend()
+    plt.title(label='KPI: '+"Number of Classrooms", loc="right", fontsize=15, fontstyle='italic')
     plt.xticks(np.arange(min_year, max_year+1, 1.0))
     plt.ylabel('Number of Classrooms')
     plt.xlabel('Year')
@@ -158,6 +162,7 @@ def total_schools_for_facilities(output_filename, input_df, state_code):
     plt.plot(df_single_teacher['Year'], df_single_teacher['total'], color='m', label='Single Teacher Schools')
 
     plt.legend()
+    plt.title(label='KPI: '+"Number of Schools", loc="right", fontsize=15, fontstyle='italic')
     plt.xticks(np.arange(min_year, max_year+1, 1.0))
     plt.ylabel('Number of Schools')
     plt.xlabel('Year')
@@ -187,6 +192,7 @@ def main_dimension_overall(output_filename, input_df, main_dimension, ylabel):
         plt.plot(df_major_repair['Year'],df_major_repair['total'],color='b', label='Need Major Repair')
     
     plt.legend()
+    plt.title(label='KPI: '+ylabel, loc="right", fontsize=15, fontstyle='italic')
     plt.xticks(np.arange(min_year, max_year+1, 1.0))
     plt.ylabel(ylabel)
     plt.xlabel('Year')
@@ -215,6 +221,7 @@ def total_schools_for_facilities_overall(output_filename, input_df):
     plt.plot(df_single_teacher['Year'], df_single_teacher['total'], color='m', label='Single Teacher Schools')
 
     plt.legend()
+    plt.title(label='KPI: '+"Number of Schools", loc="right", fontsize=15, fontstyle='italic')
     plt.xticks(np.arange(min_year, max_year+1, 1.0))
     plt.ylabel('Number of Schools')
     plt.xlabel('Year')