title updated for trend and distribution

utils.py

@@ -7,6 +7,7 @@ matplotlib.use('Agg')
 import matplotlib.pyplot as plt
 
 # dict_summary={"top3":[],"bottom3":[]}
+
 fig_size_ds_w, fig_size_ds_h = 10, 6
 fig_size_tr_w, fig_size_tr_h = 8, 6
 
@@ -40,8 +41,17 @@ def statewise_distribution(output_filename, input_df, year, ylabel, main_dimensi
     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_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)
+    if 'Facilities' in main_dimension:
+        dim = 'Dimension'
+    elif 'Qualification' in main_dimension:
+        dim = 'Educational Qualification'
+    elif 'Classroom' in main_dimension:
+        dim = 'Condition'
+    else:
+        dim = 'Category'
+    label='Year: ' + str(year) + ', ' + dim + ': ' + sub_dimension
+    plt.title(label=label, loc="right", fontsize=10, fontstyle='italic')
+    # plt.xticks(rotation=90, ha="right", fontsize=10)
     plt.yticks(fontsize=7)
     # plt.bar(df_sum['State_Name'],df_sum['total_by_population'], align='center')
     plt.barh(df_sum['State_Name'], df_sum['total_by_population'],align='center')
@@ -59,6 +69,7 @@ def total_enrolment_by_category(output_filename, input_df, main_dimension, state
     fig = plt.figure(figsize=(fig_size_tr_w,fig_size_tr_h))
     df_fil = input_df.loc[input_df['Main_Dimension'] == main_dimension]
     df_fil = df_fil.loc[(df_fil['State_Code'] == state_code)]
+    state_name = list(set(df_fil['State_Name']))[0]
     min_year, max_year = min(df_fil['Year']), max(df_fil['Year'])
     df_sum = df_fil.groupby(['Sub_Dimension','State_Code','Year'],as_index = False).sum()
     df_sum = df_sum[['Sub_Dimension','State_Code','Year','total']]
@@ -79,7 +90,7 @@ def total_enrolment_by_category(output_filename, input_df, main_dimension, state
             plt.text(x = x, y = y, s = '{:.0f}'.format(y), color='b', rotation=15, fontsize=7, weight='bold')
     
     plt.legend()
-    plt.title(label='KPI: '+ylabel, loc="right", fontsize=15, fontstyle='italic')
+    plt.title(label='State: ' + state_name + ', Type: ' + main_dimension, loc="right", fontsize=10, fontstyle='italic')
     plt.xticks(np.arange(min_year, max_year+1, 1.0))
     plt.ylabel(ylabel)
     plt.xlabel('Year')
@@ -90,6 +101,7 @@ def total_teachers_by_main_dimension(output_filename, input_df, main_dimension,
     fig = plt.figure(figsize=(fig_size_tr_w,fig_size_tr_h))
     df_fil = input_df.loc[input_df['Main_Dimension'] == main_dimension]
     df_fil = df_fil.loc[(df_fil['State_Code'] == state_code)]
+    state_name = list(set(df_fil['State_Name']))[0]
     min_year, max_year = min(df_fil['Year']), max(df_fil['Year'])
     df_sum = df_fil.groupby(['Sub_Dimension','State_Code','Year'],as_index = False).sum()
     df_sum = df_sum[['Sub_Dimension','State_Code','Year','total']]
@@ -124,7 +136,7 @@ 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.title(label='State: ' + state_name + ', Type: ' + main_dimension, loc="right", fontsize=10, fontstyle='italic')
     plt.xticks(np.arange(min_year, max_year+1, 1.0))
     plt.ylabel('Number of Teachers')
     plt.xlabel('Year')
@@ -135,6 +147,7 @@ def total_classrooms_by_trend(output_filename, input_df, state_code):
     fig = plt.figure(figsize=(fig_size_tr_w,fig_size_tr_h))
     df_fil=input_df.loc[input_df['Main_Dimension'] == "Total Classrooms"]
     df_fil=df_fil.loc[(df_fil['State_Code'] == state_code)]
+    state_name = list(set(df_fil['State_Name']))[0]
     min_year, max_year = min(df_fil['Year']), max(df_fil['Year'])
     df_sum = df_fil.groupby(['Sub_Dimension','State_Code','Year'],as_index = False).sum()
     df_sum = df_sum[['Sub_Dimension','State_Code','Year','total']]
@@ -154,7 +167,7 @@ def total_classrooms_by_trend(output_filename, input_df, state_code):
         plt.text(x = x, y = y, s = '{:.0f}'.format(y), color='b', rotation=15, fontsize=7, weight='bold')
 
     plt.legend()
-    plt.title(label='KPI: '+"Number of Classrooms", loc="right", fontsize=15, fontstyle='italic')
+    plt.title(label='State: ' + state_name, loc="right", fontsize=10, fontstyle='italic')
     plt.xticks(np.arange(min_year, max_year+1, 1.0))
     plt.ylabel('Number of Classrooms')
     plt.xlabel('Year')
@@ -165,6 +178,7 @@ def total_schools_for_facilities(output_filename, input_df, state_code):
     fig = plt.figure(figsize=(fig_size_tr_w,fig_size_tr_h))
     df_fil=input_df.loc[input_df['Main_Dimension'] == "School Facilities"]
     df_fil=df_fil.loc[(df_fil['State_Code'] == state_code)]
+    state_name = list(set(df_fil['State_Name']))[0]
     min_year, max_year = min(df_fil['Year']), max(df_fil['Year'])
     df_sum = df_fil.groupby(['Sub_Dimension','State_Code','Year'],as_index = False).sum()
     df_sum = df_sum[['Sub_Dimension','State_Code','Year','total']]
@@ -184,7 +198,7 @@ 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.title(label='State: ' + state_name, loc="right", fontsize=10, fontstyle='italic')
     plt.xticks(np.arange(min_year, max_year+1, 1.0))
     plt.ylabel('Number of Schools')
     plt.xlabel('Year')
@@ -226,7 +240,7 @@ def main_dimension_overall(output_filename, input_df, main_dimension, ylabel):
             plt.text(x = x, y = y, s = '{:.0f}'.format(y))
     
     plt.legend()
-    plt.title(label='KPI: '+ylabel, loc="right", fontsize=15, fontstyle='italic')
+    plt.title(label='KPI: ' + ylabel, loc="right", fontsize=10, fontstyle='italic')
     plt.xticks(np.arange(min_year, max_year+1, 1.0))
     plt.ylabel(ylabel)
     plt.xlabel('Year')
@@ -255,7 +269,7 @@ 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.title(label='KPI: Number of Schools', loc="right", fontsize=10, fontstyle='italic')
     plt.xticks(np.arange(min_year, max_year+1, 1.0))
     plt.ylabel('Number of Schools')
     plt.xlabel('Year')