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Implemented Caching in loaded datasets for Improved Performance #379

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Oct 7, 2024
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Implemented Caching in loaded datasets for Improved Performance #379

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24 changes: 15 additions & 9 deletions streamlit/home.py
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Original file line number Diff line number Diff line change
Expand Up @@ -9,17 +9,21 @@
# DATA LOADING
#######################################

st.set_page_config(layout='wide')
st.set_page_config(layout='wide')

@st.cache_data # Caching data loading functions
def load_data(url):
return pd.read_csv(url)

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

# Filter the 2020 dataframe
df2020 = df[df['SalaryUSD'] < 200000]
Expand Down Expand Up @@ -109,12 +113,14 @@
}
df_ai.replace(short_mapping, inplace=True)

@st.cache_data
def mean_salary(df):
mean_salary = df[df['SalaryUSD'] <= 1000000]['SalaryUSD'].mean()
df.loc[df['SalaryUSD'] > 1000000, 'SalaryUSD'] = mean_salary
return df

# Function to create value count plots for each column
@st.cache_data
def plot_value_counts(column_name):
colors = ['skyblue', 'yellow']
fig = px.bar(df_ai[column_name].value_counts().reset_index(), x='index', y=column_name, color_discrete_sequence=[random.choice(colors)])
Expand Down