diff gaiac_data_averaging/gaiac_dataaveraging.py @ 0:0a8233db930e draft

planemo upload for repository https://github.com/jaidevjoshi83/gaiac.git commit c29a769ed165f313a6410925be24f776652a9663-dirty

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/gaiac_data_averaging/gaiac_dataaveraging.py	Thu May 15 14:46:28 2025 +0000
@@ -0,0 +1,38 @@
+import pandas as pd
+import argparse
+
+#This tool would average your time series data based on the time intervals based on the time and date column 
+#python avg_timeseries.py -I data.tsv -C 1 -T 5 -O averaged_output.tsv
+
+
+def main():
+    parser = argparse.ArgumentParser(description="Average time series data over specified intervals.")
+    parser.add_argument("-I", "--infile", required=True, help="Input data file (TSV format)")
+    parser.add_argument("-C", "--dt_column", required=True, help="Column number (1-based) for the DateTime column")
+    parser.add_argument("-T", "--time_interval", required=True, help="Time interval in minutes, e.g., '5' or '30'")
+    parser.add_argument("-O", "--out_file", default='OutFile.tsv', help="Output file name (TSV format)")
+    parser.add_argument("-S", "--sep", default='\t', help="deliminator")
+
+    args = parser.parse_args()
+
+    # Load data
+    data = pd.read_csv(args.infile, sep=args.sep)
+
+    # Extract the correct datetime column name
+    col_index = int(args.dt_column) - 1  # Convert 1-based index to 0-based
+    datetime_col = data.columns[col_index]
+
+    # Set datetime index
+    data[datetime_col] = pd.to_datetime(data[datetime_col], errors='coerce')
+    data.set_index(datetime_col, inplace=True)
+
+    # Group by time intervals and compute mean for numeric columns
+    df_avg = data.resample(f'{args.time_interval}Min').mean(numeric_only=True)
+
+    # Round to 3 decimals and save to output file
+    df_avg.round(3).to_csv(args.out_file, sep='\t')
+
+    print(f"Averaged data saved to {args.out_file}")
+
+if __name__ == "__main__":
+    main()