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Issue #382 fixed StreamlitDuplicateElementId #400

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merged 2 commits into from
Oct 16, 2024
Merged

Issue #382 fixed StreamlitDuplicateElementId #400

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861773b
have removed the StreamlitDuplicateElementId Issue #382
A-Akhil Oct 15, 2024
2b3fb35
changed from local file to github csv fetch #382
A-Akhil Oct 15, 2024
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2 changes: 2 additions & 0 deletions .gitignore
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Original file line number Diff line number Diff line change
@@ -1,2 +1,4 @@
catboost_info/
venv/
.venv/
streamlit\__pycache__
Binary file modified streamlit/__pycache__/functions.cpython-312.pyc
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Binary file modified streamlit/__pycache__/main_analysis.cpython-312.pyc
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19 changes: 17 additions & 2 deletions streamlit/functions.py
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Expand Up @@ -20,6 +20,21 @@
results = pd.read_csv("https://raw.githubusercontent.com/Recode-Hive/Stackoverflow-Analysis/main/streamlit/results.csv")


# Load the data from local CSV files
# data = pd.read_csv('df2020.csv')
# df2018 = pd.read_csv('df2018.csv')
# full_data2018 = pd.read_csv('survey_results_sample_2018.csv')
# full_data2019 = pd.read_csv('survey_results_sample_2019.csv')
# full_df2020 = pd.read_csv('survey_results_sample_2020.csv')
# df2019 = pd.read_csv('df2019.csv')

# # Filter the 2020 data
# df2020 = data[(data['SalaryUSD'] < 200000)]

# # Load results for job satisfaction from the local file
# results = pd.read_csv("results.csv")


#######################################
# VISUALISATION STARTS
#######################################
Expand All @@ -35,7 +50,7 @@ def plot_boxplot(data, x, y, title):

#########################################################################

def plot_bar_plotly(df, column_name, top_n=10, height=450, width=700):
def plot_bar_plotly(df, column_name, top_n=10, height=450, width=700, key=None):
df_counts = df[column_name].value_counts().head(top_n).reset_index()
df_counts.columns = [column_name, 'Count']

Expand All @@ -46,7 +61,7 @@ def plot_bar_plotly(df, column_name, top_n=10, height=450, width=700):
fig.update_layout(xaxis_title=column_name, yaxis_title='Number of Developers')
fig.update_layout(height=height, width=width)

return st.plotly_chart(fig)
return st.plotly_chart(fig, key=key)


def plot_pie_plotly(df, column_name,top_n=10, height=400, width=400 ):
Expand Down
36 changes: 23 additions & 13 deletions streamlit/home.py
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Expand Up @@ -16,14 +16,24 @@ def load_data(url):
return pd.read_csv(url)

# Loading data files from the 'streamlit' directory
df = load_data('https://raw.githubusercontent.com/Recode-Hive/Stackoverflow-Analysis/main/streamlit/df2020.csv')
df2018 = load_data('https://raw.githubusercontent.com/Recode-Hive/Stackoverflow-Analysis/main/streamlit/df2018.csv')
full_data2018 = load_data('https://raw.githubusercontent.com/Recode-Hive/Stackoverflow-Analysis/main/streamlit/survey_results_sample_2018.csv')
full_data2019 = load_data('https://raw.githubusercontent.com/Recode-Hive/Stackoverflow-Analysis/main/streamlit/survey_results_sample_2019.csv')
full_df2020 = load_data('https://raw.githubusercontent.com/Recode-Hive/Stackoverflow-Analysis/main/streamlit/survey_results_sample_2020.csv')
df2019 = load_data('https://raw.githubusercontent.com/Recode-Hive/Stackoverflow-Analysis/main/streamlit/df2019.csv')
df2021 = load_data('https://raw.githubusercontent.com/Recode-Hive/Stackoverflow-Analysis/main/streamlit/df2021.csv')
df2022 = load_data('https://raw.githubusercontent.com/Recode-Hive/Stackoverflow-Analysis/main/streamlit/df2022.csv')
# df = load_data('https://raw.githubusercontent.com/Recode-Hive/Stackoverflow-Analysis/main/streamlit/df2020.csv')
# df2018 = load_data('https://raw.githubusercontent.com/Recode-Hive/Stackoverflow-Analysis/main/streamlit/df2018.csv')
# full_data2018 = load_data('https://raw.githubusercontent.com/Recode-Hive/Stackoverflow-Analysis/main/streamlit/survey_results_sample_2018.csv')
# full_data2019 = load_data('https://raw.githubusercontent.com/Recode-Hive/Stackoverflow-Analysis/main/streamlit/survey_results_sample_2019.csv')
# full_df2020 = load_data('https://raw.githubusercontent.com/Recode-Hive/Stackoverflow-Analysis/main/streamlit/survey_results_sample_2020.csv')
# df2019 = load_data('https://raw.githubusercontent.com/Recode-Hive/Stackoverflow-Analysis/main/streamlit/df2019.csv')
# df2021 = load_data('https://raw.githubusercontent.com/Recode-Hive/Stackoverflow-Analysis/main/streamlit/df2021.csv')
# df2022 = load_data('https://raw.githubusercontent.com/Recode-Hive/Stackoverflow-Analysis/main/streamlit/df2022.csv')

df = load_data('df2020.csv')
df2018 = load_data('df2018.csv')
full_data2018 = load_data('survey_results_sample_2018.csv')
full_data2019 = load_data('survey_results_sample_2019.csv')
full_df2020 = load_data('survey_results_sample_2020.csv')
df2019 = load_data('df2019.csv')
df2021 = load_data('df2021.csv')
df2022 = load_data('df2022.csv')


# Filter the 2020 dataframe
df2020 = df[df['SalaryUSD'] < 200000]
Expand Down Expand Up @@ -136,7 +146,7 @@ def plot_value_counts(column_name):

if year == '2018':
main.main_analysis(df2018)
main.main_analysis_2(df2018)
main.main_analysis_2(df2018, year)

visual, analysis = st.columns((3, 1))
with visual:
Expand Down Expand Up @@ -209,7 +219,7 @@ def plot_value_counts(column_name):

elif year == '2019':
main.main_analysis(df2019)
main.main_analysis_2(df2019)
main.main_analysis_2(df2019, year)

visual, analysis = st.columns((3, 1))
with visual:
Expand All @@ -228,7 +238,7 @@ def plot_value_counts(column_name):

elif year == '2020':
main.main_analysis(df2020)
main.main_analysis_2(df2020)
main.main_analysis_2(df2020, year)

visual, analysis = st.columns((3, 1))
with visual:
Expand All @@ -247,7 +257,7 @@ def plot_value_counts(column_name):

elif year == '2021':
main.main_analysis(df2021)
main.common_analysis_2021_2022(df2021)
main.common_analysis_2021_2022(df2021, year)
visual, analysis = st.columns((3, 1))
with visual:
fig = func.plot_valuecounts_plotly(df2021,'NEWStuck')
Expand Down Expand Up @@ -281,7 +291,7 @@ def plot_value_counts(column_name):

else:
main.main_analysis(df2022)
main.common_analysis_2021_2022(df2022)
main.common_analysis_2021_2022(df2022, year)

fig = func.compare_language_columns_and_plot(df2022, 'OpSysPersonal use', 'OpSysProfessional use')

Expand Down
12 changes: 6 additions & 6 deletions streamlit/main_analysis.py
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Expand Up @@ -103,7 +103,7 @@ def main_analysis(df):

with visual:
st.title("Ethnicity VS Participation")
ff.plot_bar_plotly(df, 'Ethnicity')
ff.plot_bar_plotly(df, 'Ethnicity', key='ethnicity_plot')

with analysis:
Ethnicity_text = """
Expand Down Expand Up @@ -176,7 +176,7 @@ def main_analysis(df):
if ds is not None:
with visual:
st.title("Country Wise Data Scientists Participation")
ff.plot_bar_plotly(ds, "Country")
ff.plot_bar_plotly(ds, "Country", key='country_plot')

with analysis:
data_scientist_participation_text = """
Expand All @@ -196,7 +196,7 @@ def main_analysis(df):
##### To Speed Up the Web Page, Main Analysis is divided into 2 ######


def main_analysis_2(df):
def main_analysis_2(df, year):
visual2, analysis2 = st.columns((3,1))

if df is df2019:
Expand Down Expand Up @@ -262,7 +262,8 @@ def main_analysis_2(df):
if ds is not None:
with visual2:
st.title("Country Wise Data Scientists Participation")
ff.plot_bar_plotly(ds, "Country")
# Use the year parameter instead of year_variable
ff.plot_bar_plotly(ds, "Country", key=f'country_plot_{year}')

with analysis2:
data_scientist_participation_text = """
Expand Down Expand Up @@ -368,7 +369,7 @@ def common_analysis_2021_2022(df):
st.markdown(employment_text, unsafe_allow_html=True)

with visual3:
ff.plot_bar_plotly(df, 'DevType', top_n=10, height=500, width=1000)
ff.plot_bar_plotly(df, 'DevType', top_n=10, height=500, width=1000, key=f'devtype_plot_{year_variable}')

with analysis3:
devtype_text = """
Expand Down Expand Up @@ -429,4 +430,3 @@ def common_analysis_2021_2022(df):
</div>
"""
st.markdown(webframe_text, unsafe_allow_html=True)