Merge pull request #285 from SDprogramer/SDbranch

Home.py and main_analysis.py changed
recodehive · Jun 19, 2024 · 20d4f75 · 20d4f75
2 parents c8574ff + 80d9821
commit 20d4f75
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diff --git a/streamlit/__pycache__/functions.cpython-312.pyc b/streamlit/__pycache__/functions.cpython-312.pyc
diff --git a/streamlit/__pycache__/main_analysis.cpython-312.pyc b/streamlit/__pycache__/main_analysis.cpython-312.pyc
diff --git a/streamlit/home.py b/streamlit/home.py
@@ -130,7 +130,7 @@ def plot_value_counts(column_name):
         highest_paying_ds_text = """
         <div class='analysis-container'>
             <div class='analysis-title'>Analysis: Data Scientist Market</div>
-            <div class='analysis-text'>
+            <div class='analysis-text' style="color: red; font-weight: bold;">
                 The top three countries with the highest mean annual salary of a data scientist are South Korea (253,315) in 2018, Ireland (275,851) in 2019, and the USA (118,863) in 2020. Apart from that, the mean salary of the rest of the countries is less than 200,000 per year. Japan provides the highest mean annual salary among Asian countries (118,969). Figures in Dollars $.
             </div>
         </div>
@@ -144,7 +144,7 @@ def plot_value_counts(column_name):
         operating_text = """
         <div class='analysis-container'>
             <div class='analysis-title'>Analysis: Operating Systems</div>
-            <div class='analysis-text'>
+            <div class='analysis-text' style="color: red; font-weight: bold;">
                 Windows is the dominating operating system used by people. OS and Linux are almost tied. The knowledge about the operating system can help developers decide to whom their audience is catered towards.
             </div>
         </div>
@@ -159,12 +159,12 @@ def plot_value_counts(column_name):
         top_ide_text = """
         <div class='analysis-container'>
             <div class='analysis-title'>Analysis: Top IDEs</div>
-            <div class='analysis-text'>
+            <div class='analysis-text' style="color: red; font-weight: bold;">
                 1.<b>Popular IDEs</b>: Visual Studio Code, Visual Studio, and Notepad++ are among the most widely used IDEs, with high user counts ranging from 25,870 to 26,280.
-                \n2.<b>Text Editors</b>: Sublime Text, Vim, and IntelliJ are also popular choices, with user counts ranging from 19,477 to 21,810.
-                \n3.<b>General-purpose Editors</b>: TextMate, Coda, and Light Table are also used, although they have lower user counts compared to other IDEs.
-                \n4.<b>Emerging Trends</b>: IPython / Jupyter, Atom, and Emacs show significant adoption, indicating a growing interest in interactive computing environments, lightweight editors, and customizable text editors, respectively.
-                \n5.<b>Industry Standard</b>: Xcode, primarily used for macOS and iOS development, maintains a substantial user base due to its integration with Apple's development ecosystem.
+                <br>2.<b>Text Editors</b>: Sublime Text, Vim, and IntelliJ are also popular choices, with user counts ranging from 19,477 to 21,810.
+                <br>3.<b>General-purpose Editors</b>: TextMate, Coda, and Light Table are also used, although they have lower user counts compared to other IDEs.
+                <br>4.<b>Emerging Trends</b>: IPython / Jupyter, Atom, and Emacs show significant adoption, indicating a growing interest in interactive computing environments, lightweight editors, and customizable text editors, respectively.
+                <br>5.<b>Industry Standard</b>: Xcode, primarily used for macOS and iOS development, maintains a substantial user base due to its integration with Apple's development ecosystem.
             </div>
         </div>
         """
@@ -173,19 +173,19 @@ def plot_value_counts(column_name):
     func.ai_graphs()
 
     ai_text = """
-    <div class='analysis-container-extra'>
+    <div class='analysis-container-extra' style="color: red; font-weight: bold;">
         <div class='analysis-title'>Analysis: AI Perception</div>
-        <div class='analysis-text'>
+        <div class='analysis-text' style="color: red; font-weight: bold;">
             1.<b>AIDangerous</b>: The most commonly cited concern is "Algorithms making important decisions," followed closely by "Artificial intelligence surpassing human intelligence" and "Evolving definitions of fairness."
             "Increasing automation of jobs" is also a significant concern but appears to be less frequently mentioned compared to the other categories.
-            \n2.<b>AIInteresting</b>: The most interesting aspect for respondents seems to be "Increasing automation of jobs," followed by "Algorithms making important decisions" and "Artificial intelligence surpassing human intelligence."
+            <br>2.<b>AIInteresting</b>: The most interesting aspect for respondents seems to be "Increasing automation of jobs," followed by "Algorithms making important decisions" and "Artificial intelligence surpassing human intelligence."
             "Evolving definitions of fairness" appears to be less intriguing to respondents compared to other categories.
-            \n3.<b>AIResponsible</b>: The majority of respondents believe that responsibility lies with "The developers or the people creating the AI."
+            <br>3.<b>AIResponsible</b>: The majority of respondents believe that responsibility lies with "The developers or the people creating the AI."
             Fewer respondents attribute responsibility to "A governmental or other regulatory body," "Prominent industry leaders," or "Nobody."
-            \n4.<b>AIFuture</b>: A significant proportion of respondents express excitement about the future of AI, indicating that they are "Excited about the possibilities more than worried about the dangers."
+            <br>4.<b>AIFuture</b>: A significant proportion of respondents express excitement about the future of AI, indicating that they are "Excited about the possibilities more than worried about the dangers."
             However, there is also a notable percentage of respondents who are "Worried about the dangers more than excited about the possibilities."
             A smaller portion of respondents either "Don't care about it" or "Haven't thought about it."
-            \n5.Overall, these results suggest a complex and varied perspective on AI technology. While many see great potential in AI, there are also concerns about its implications, particularly regarding decision-making, automation of jobs, and the ethical considerations surrounding its development and regulation.
+            <br>5.Overall, these results suggest a complex and varied perspective on AI technology. While many see great potential in AI, there are also concerns about its implications, particularly regarding decision-making, automation of jobs, and the ethical considerations surrounding its development and regulation.
         </div>
     </div>
     """
@@ -202,7 +202,7 @@ def plot_value_counts(column_name):
         highest_paying_ds_text = """
         <div class='analysis-container'>
             <div class='analysis-title'>Analysis: Data Scientist Market</div>
-            <div class='analysis-text'>
+            <div class='analysis-text' style="color: red; font-weight: bold;">
                 The top three countries with the highest mean annual salary of a data scientist are South Korea (253,315) in 2018, Ireland (275,851) in 2019, and the USA (118,863) in 2020. Apart from that, the mean salary of the rest of the countries is less than 200,000 per year. Japan provides the highest mean annual salary among Asian countries (118,969). Figures in Dollars $.
             </div>
         </div>
@@ -220,7 +220,7 @@ def plot_value_counts(column_name):
         highest_paying_ds_text = """
         <div class='analysis-container'>
             <div class='analysis-title'>Analysis: Data Scientist Market</div>
-            <div class='analysis-text'>
+            <div class='analysis-text' style="color: red; font-weight: bold;">
                 The top three countries with the highest mean annual salary of a data scientist are South Korea (253,315) in 2018, Ireland (275,851) in 2019, and the USA (118,863) in 2020. Apart from that, the mean salary of the rest of the countries is less than 200,000 per year. Japan provides the highest mean annual salary among Asian countries (118,969). Figures in Dollars $.
             </div>
         </div>

diff --git a/streamlit/main_analysis.py b/streamlit/main_analysis.py
@@ -40,7 +40,7 @@ def main_analysis(df):
     annual_salary_top_text = """
     <div class='analysis-container-extra'>
         <div class='analysis-title'>Analysis: Distribution of Annual Salary for Top Countries</div>
-        <div class='analysis-text'>
+        <div class='analysis-text' style="color: red; font-weight: bold;">
             Overall, the country which has the highest mean annual salary is the United States of America(240,000) Dollars. The second highest country which provides the highest mean salary is Australia(164,926) Dollars. Though India has a higher number of respondents, it has the lowest mean salary of $25,213.We can understand that the mean salary of a developed country is much higher than that of a developing country.
         </div>
     </div>
@@ -57,7 +57,7 @@ def main_analysis(df):
         geographical_text = """
     <div class='analysis-container'>
         <div class='analysis-title'>Analysis: Geographical plot to show number of respondents in each country</div>
-        <div class='analysis-text'>
+        <div class='analysis-text' style="color: red; font-weight: bold;">
             The geographical plot shows the number of respondents by country, with the United States having the highest participation. Other countries with significant participation include India, Brazil, and several European nations. The intensity of color represents the number of respondents, with darker shades indicating higher numbers.
         </div>
     </div>
@@ -73,7 +73,7 @@ def main_analysis(df):
         income_gender_text = """
         <div class='analysis-container'>
             <div class='analysis-title'>Analysis: Income vs Gender</div>
-            <div class='analysis-text'>
+            <div class='analysis-text' style="color: red; font-weight: bold;">
                 There is a little bit of difference between Gender and income they received respectively. 
                 Men tend to receive more salary than women from the above analysis.
             </div>
@@ -90,7 +90,7 @@ def main_analysis(df):
         Ethnicity_text = """
         <div class='analysis-container'>
             <div class='analysis-title'>Analysis: Ethnicity vs Participation</div>
-            <div class='analysis-text'>
+            <div class='analysis-text' style="color: red; font-weight: bold;">
                 From the Survey Analysis, more participation has been happened from White or of European Ethnicity.
                 The least has been recorded as only 0.16% from Indigenous. The second top survey contributors are from South Asians which is 11.93% of the respondents..
             </div>
@@ -107,7 +107,7 @@ def main_analysis(df):
             age_text = """
             <div class='analysis-container-extra'>
                 <div class='analysis-title'>Analysis: Distribution of respondents based on age</div>
-                <div class='analysis-text'>
+                <div class='analysis-text' style="color: red; font-weight: bold;">
                     Late twenties respondents are clearly dominating the survey responses. It could be the age-range of a typical user on StackOverflow website.
                     The graph is plotted in a descending order for better visuality, and understanding.
             </div>
@@ -122,7 +122,7 @@ def main_analysis(df):
         gender_top_country_text = """
     <div style='margin-top: 400px !important' class='analysis-container'>
         <div class='analysis-title'>Analysis: Men vs Women Participation</div>
-        <div class='analysis-text'>
+        <div class='analysis-text' style="color: red; font-weight: bold;">
             Women participation is extremely low in the STEM field, compared to men. They are even less than 20% of total male population that is dominating the tech industry in almost all the countries.
         </div>
     </div>
@@ -137,9 +137,9 @@ def main_analysis(df):
         LanguageDesireNextYear_text = """
         <div class='analysis-container'>
             <div class='analysis-title'>Analysis: Programming language desired to work</div>
-            <div class='analysis-text'>
-                In 2019, respondents said that they wanted to work in javascript is around more than 10 % and the fewer respond have a desire to work on VBA next year. People started to work in Haskell, Julia, and pearl in 2019 though the amount was less around 5% of people have the desire to work in those languages in 2021. Here, phyton is the 2nd one in which people have the desire to work in both 2019 and 2020.
-                \n However, if we look at the big picture, Python has been constantly gaining significant popularity within the developers community for three consequent years, whereas JavaScript is either constant or decling in popularity.
+            <div class='analysis-text' style="color: red; font-weight: bold;">
+                In 2019, respondents said that they wanted to work in javascript is around more than 10 % and the fewer respond have a desire to work on VBA next year. People started to work in Haskell, Julia, and pearl in 2019 though the amount was less around 5% of people have the desire to work in those languages in 2021. Here, python is the 2nd one in which people have the desire to work in both 2019 and 2020.
+                <br>However, if we look at the big picture, Python has been constantly gaining significant popularity within the developers community for three consequent years, whereas JavaScript is either constant or decling in popularity.
         </div>
     """
         st.markdown(LanguageDesireNextYear_text, unsafe_allow_html=True)
@@ -160,9 +160,9 @@ def main_analysis(df):
     education_salary_text = """
             <div class='analysis-container-extra'>
                 <div class='analysis-title'>Analysis: Programming language desired to work</div>
-                <div class='analysis-text'>
+                <div class='analysis-text' style="color: red; font-weight: bold;">
                     As we can see, the respondents who have done Doctorate have the highest mean salary among all other education levels. Secondly, the respondents who have done Bachelors degree have more salary than that of Masters degree holders. This may be due to years of professional coding experience and due to the higher number of respondents in that category than that of Masters degree
-                    \nThe most interesting is that the respondents who do not have any degree have a mean salary of $90k. This shows the improvement in online learning and advancement of technology that is shifting the company from relying on University degrees.
+                    <br>The most interesting is that the respondents who do not have any degree have a mean salary of $90k. This shows the improvement in online learning and advancement of technology that is shifting the company from relying on University degrees.
             </div>
         """
     st.markdown(education_salary_text, unsafe_allow_html=True)
@@ -175,9 +175,9 @@ def main_analysis(df):
         devtype_text = """
         <div style='margin-top: 400px !important' class='analysis-container'>
             <div class='analysis-title'>Analysis: Distribution of surveyors based on their developer role</div>
-            <div class='analysis-text'>
+            <div class='analysis-text' style="color: red; font-weight: bold;">
                 Based on respondents responses the survey concluded that they wanted to work in JavaScript is around more than 10%, and fewer respondents have a desire to work on VBA next year. People started to work in Haskell, Julia, and Pearl in 2019, though the amount was less; around 5% of people have the desire to work in those languages in 2021. Here, Python is the 2nd one in which people have the desire to work in both 2019 and 2020.
-                \nHowever, if we look at the big picture, Python has been constantly gaining significant popularity within the developer community for three consequent years, whereas JavaScript is either constant or declining in popularity.
+                <br>However, if we look at the big picture, Python has been constantly gaining significant popularity within the developer community for three consequent years, whereas JavaScript is either constant or declining in popularity.
             </div>
         </div>
     """
@@ -205,7 +205,7 @@ def main_analysis(df):
         data_scientist_participation_text = """
     <div style='margin-top: 400px !important' class='analysis-container'>
         <div class='analysis-title'>Analysis: Data Scientist Market</div>
-        <div class='analysis-text'>
+        <div class='analysis-text' style="color: red; font-weight: bold;">
             There are many data scientists who responded to the Stackoverflow survey. Most data scientists are from the US around 1,500-1700 people and it is 3 times higher than data scientists from India. Followed by Germany and the UK with 427 and 339 people respectively. The rest are Canada, France, Netherlands, Brazil, Russia, and Australia which have less than 200 data scientists.
         </div>
     </div>
@@ -230,7 +230,7 @@ def main_analysis(df):
         highest_paying_ds_text = """
     <div style='margin-top: 400px !important' class='analysis-container'>
         <div class='analysis-title'>Analysis: Data Scientist Market</div>
-        <div class='analysis-text'>
+        <div class='analysis-text' style="color: red; font-weight: bold;">
             The top  countries which have a highest mean annual salary of a data scientist are South Korea (253,315) in 2018,Ireland (275,851) in 2019, and the USA(118,863) in 2020. Apart from that, the mean salary of the rest of the countries is less than (200,000) per year. Japan provides the highest mean annual salary among Asian countries (118,969)
             Figures in Dollars $
         </div>
@@ -247,7 +247,7 @@ def main_analysis(df):
               jobsatis_text = """
     <div style='margin-top: 400px !important' class='analysis-container'>
         <div class='analysis-title'>Analysis: Data Scientist Market</div>
-        <div class='analysis-text'>
+        <div class='analysis-text' style="color: red; font-weight: bold;">
             In 2019, the top three countries which have a highest mean annual salary of a data scientist are Ireland (275,851), Luxembourg (272,769), and the USA (265,211). Apart from that, the mean salary of the rest of the countries is less than (200,000) per year. Japan provides the highest mean annual salary among Asian countries (118,969)
             Figures in Dollars $
         </div>
@@ -262,7 +262,7 @@ def main_analysis(df):
         feature_jobsatis_text = """
     <div style='margin-top: 400px !important' class='analysis-container'>
         <div class='analysis-title'>Analysis: Features for Job Satisfaction</div>
-        <div class='analysis-text'>
+        <div class='analysis-text' style="color: red; font-weight: bold;">
             The top 2 features negatively affecting Job Satisfaction are age, country. So, in the elderly ages, job satisfaction may decrease because of the personal expectation increases. In the same way, as the professional coding years are increasing, satisfaction may decrease.
             Among the countries; most dissatisfied countries are Angolia, Rwanda, Krygyzstan, Sudan.
             UndergradMajor and other Science, are mostly satisfied.