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| 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() |