import pandas as pd import streamlit as st def transform_data(df): # Transform 'respond' variable respond_mapping = { "Parent": 1, "Teacher": 2, "Self": 3, "Other": 4, "Significant other": 5, "Parent 1": 6, "Parent 2": 7, "Not available": 999 } if 'respond' in df: df['respond'] = df['respond'].map(respond_mapping) # Transform 'sri_ts' and 'sld_ts' variables sri_sld_values = { 8: 36.6, 9: 42.1, 10: 44.8, 11: 46.8, 12: 48.5, 13: 50.0, 14: 51.3, 15: 52.5, 16: 53.7, 17: 54.9, 18: 56.0, 19: 57.1, 20: 58.2, 21: 59.3, 22: 60.3, 23: 61.4, 24: 62.4, 25: 63.5, 26: 64.5, 27: 65.6, 28: 66.6, 29: 67.6, 30: 68.7, 31: 69.7, 32: 70.7, 33: 71.8, 34: 72.9, 35: 74.1, 36: 75.4, 37: 76.8, 38: 78.5, 39: 80.3, 40: 82.7 } if 'sri_rs' in df.columns: df['sri_ts'] = df['sri_rs'].map(sri_sld_values).fillna("NA") if 'sld_rs' in df.columns: df['sld_ts'] = df['sld_rs'].map(sri_sld_values).fillna("NA") # Transform 'dsm_cross_ch' variables dsm_cross_ch_cols = [f'dsm_cross_ch{num}' for num in range(20, 26)] for col in dsm_cross_ch_cols: if col in df: df[col] = df[col].map({0: 2, 1: 1}) # Transform 'dsm_cross_pg' variables dsm_cross_pg_cols = [f'dsm_cross_pg{num}' for num in range(20, 26)] for col in dsm_cross_pg_cols: if col in df: df[col] = df[col].map({0: 1, 1: 2, 2: -9}) # Transform 'rcads_y' variables rcads_y_cols = [f'rcads_y{num}' for num in range(14, 27)] for col in rcads_y_cols: if col in df: df[col] = df[col] + 1 # Ensure rcads_y26 exists and set default values if 'rcads_y26' not in df: df['rcads_y26'] = 1 # Return transformed dataframe return df def main(): st.title("Data Transformation App") uploaded_file = st.file_uploader("Upload CSV or Excel file", type=['csv', 'xlsx']) if uploaded_file: # Determine the file type and read data accordingly if uploaded_file.name.endswith('.csv'): df = pd.read_csv(uploaded_file) elif uploaded_file.name.endswith('.xlsx'): df = pd.read_excel(uploaded_file) # Transform the data transformed_df = transform_data(df) # Display transformed data st.write("Transformed Data:") st.dataframe(transformed_df) # Download link for transformed data st.download_button( label="Download Transformed Data", data=transformed_df.to_csv(index=False).encode('utf-8'), file_name='transformed_data.csv', mime='text/csv', ) if __name__ == '__main__': main()