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Education in INDIA
Commit a5f5ed7e authored by Manas Gabani's avatar Manas Gabani
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title updated for trend and distribution

parent e4340300
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Showing with 22 additions and 8 deletions
utils.py
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...@@ -7,6 +7,7 @@ matplotlib.use('Agg') ...@@ -7,6 +7,7 @@ matplotlib.use('Agg')
import matplotlib.pyplot as plt import matplotlib.pyplot as plt
# dict_summary={"top3":[],"bottom3":[]} # dict_summary={"top3":[],"bottom3":[]}
fig_size_ds_w, fig_size_ds_h = 10, 6 fig_size_ds_w, fig_size_ds_h = 10, 6
fig_size_tr_w, fig_size_tr_h = 8, 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 ...@@ -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) 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)) fig = plt.figure(figsize=(fig_size_ds_w,fig_size_ds_h))
plt.title(label='KPI: '+ylabel, loc="right", fontsize=15, fontstyle='italic') if 'Facilities' in main_dimension:
# plt.xticks(rotation=90, ha="right", fontsize=8) 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.yticks(fontsize=7)
# plt.bar(df_sum['State_Name'],df_sum['total_by_population'], align='center') # 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') 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 ...@@ -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)) 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 = input_df.loc[input_df['Main_Dimension'] == main_dimension]
df_fil = df_fil.loc[(df_fil['State_Code'] == state_code)] 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']) 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_fil.groupby(['Sub_Dimension','State_Code','Year'],as_index = False).sum()
df_sum = df_sum[['Sub_Dimension','State_Code','Year','total']] 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 ...@@ -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.text(x = x, y = y, s = '{:.0f}'.format(y), color='b', rotation=15, fontsize=7, weight='bold')
plt.legend() 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.xticks(np.arange(min_year, max_year+1, 1.0))
plt.ylabel(ylabel) plt.ylabel(ylabel)
plt.xlabel('Year') plt.xlabel('Year')
...@@ -90,6 +101,7 @@ def total_teachers_by_main_dimension(output_filename, input_df, main_dimension, ...@@ -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)) 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 = input_df.loc[input_df['Main_Dimension'] == main_dimension]
df_fil = df_fil.loc[(df_fil['State_Code'] == state_code)] 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']) 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_fil.groupby(['Sub_Dimension','State_Code','Year'],as_index = False).sum()
df_sum = df_sum[['Sub_Dimension','State_Code','Year','total']] 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, ...@@ -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.plot(df_phd['Year'],df_phd['total'],color='m', label='M.Phil / Ph.D')
plt.legend() 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.xticks(np.arange(min_year, max_year+1, 1.0))
plt.ylabel('Number of Teachers') plt.ylabel('Number of Teachers')
plt.xlabel('Year') plt.xlabel('Year')
...@@ -135,6 +147,7 @@ def total_classrooms_by_trend(output_filename, input_df, state_code): ...@@ -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)) 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=input_df.loc[input_df['Main_Dimension'] == "Total Classrooms"]
df_fil=df_fil.loc[(df_fil['State_Code'] == state_code)] 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']) 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_fil.groupby(['Sub_Dimension','State_Code','Year'],as_index = False).sum()
df_sum = df_sum[['Sub_Dimension','State_Code','Year','total']] 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): ...@@ -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.text(x = x, y = y, s = '{:.0f}'.format(y), color='b', rotation=15, fontsize=7, weight='bold')
plt.legend() 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.xticks(np.arange(min_year, max_year+1, 1.0))
plt.ylabel('Number of Classrooms') plt.ylabel('Number of Classrooms')
plt.xlabel('Year') plt.xlabel('Year')
...@@ -165,6 +178,7 @@ def total_schools_for_facilities(output_filename, input_df, state_code): ...@@ -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)) 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=input_df.loc[input_df['Main_Dimension'] == "School Facilities"]
df_fil=df_fil.loc[(df_fil['State_Code'] == state_code)] 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']) 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_fil.groupby(['Sub_Dimension','State_Code','Year'],as_index = False).sum()
df_sum = df_sum[['Sub_Dimension','State_Code','Year','total']] 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): ...@@ -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.plot(df_single_teacher['Year'], df_single_teacher['total'], color='m', label='Single Teacher Schools')
plt.legend() 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.xticks(np.arange(min_year, max_year+1, 1.0))
plt.ylabel('Number of Schools') plt.ylabel('Number of Schools')
plt.xlabel('Year') plt.xlabel('Year')
...@@ -226,7 +240,7 @@ def main_dimension_overall(output_filename, input_df, main_dimension, ylabel): ...@@ -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.text(x = x, y = y, s = '{:.0f}'.format(y))
plt.legend() 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.xticks(np.arange(min_year, max_year+1, 1.0))
plt.ylabel(ylabel) plt.ylabel(ylabel)
plt.xlabel('Year') plt.xlabel('Year')
...@@ -255,7 +269,7 @@ def total_schools_for_facilities_overall(output_filename, input_df): ...@@ -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.plot(df_single_teacher['Year'], df_single_teacher['total'], color='m', label='Single Teacher Schools')
plt.legend() 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.xticks(np.arange(min_year, max_year+1, 1.0))
plt.ylabel('Number of Schools') plt.ylabel('Number of Schools')
plt.xlabel('Year') plt.xlabel('Year')
......
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