|
import csv |
|
from pathlib import Path |
|
import numpy as np |
|
import pandas as pd |
|
|
|
from collections import defaultdict |
|
|
|
FULL_DATA_SET_STRING = "../full_years_remove_flawed_rows.csv" |
|
FULL_DATA_SET_PATH = Path(FULL_DATA_SET_STRING) |
|
OUT_DATASET_STRING = "../trimmed_full_years_for_db.parquet" |
|
OUT_DATASET_PATH = Path(OUT_DATASET_STRING) |
|
OUT_FULL_DATASET_STRING = "../full_years_remove_flawed.parquet" |
|
OUT_FULL_DATASET_PATH = Path(OUT_FULL_DATASET_STRING) |
|
|
|
NUMERIC_FIELDS = ["WSPD","GST","WVHT","DPD","APD","PRES","ATMP","WTMP"] |
|
|
|
|
|
def load_data(data_path): |
|
print("Loading data") |
|
|
|
with open(data_path, newline='') as csv_file: |
|
|
|
loaded_np_data = pd.read_csv(csv_file) |
|
|
|
print("Writing out the full Parquet file") |
|
loaded_np_data.to_parquet(OUT_FULL_DATASET_PATH) |
|
|
|
print("Applying Sin() to the two degrees columns") |
|
loaded_np_data["WDIR"] = np.sin(np.deg2rad(loaded_np_data["WDIR"])) |
|
loaded_np_data["MWD"] = np.sin(np.deg2rad(loaded_np_data["MWD"])) |
|
|
|
print("calculating z-scores") |
|
for var in NUMERIC_FIELDS: |
|
var_mean = np.mean(loaded_np_data[var]) |
|
var_std = np.std(loaded_np_data[var]) |
|
|
|
var_zscore = (loaded_np_data[var] - var_mean)/var_std |
|
loaded_np_data[var] = var_zscore |
|
|
|
print("finding outlier rows") |
|
|
|
|
|
|
|
|
|
output_np_data = loaded_np_data[loaded_np_data[NUMERIC_FIELDS].gt(2).sum(axis=1).lt(2)] |
|
|
|
print("exporting to parquet") |
|
output_np_data.set_index("TSTMP") |
|
output_np_data.to_parquet(OUT_DATASET_PATH) |
|
|
|
|
|
if __name__ == '__main__': |
|
print("Start") |
|
|
|
|
|
all_data = load_data(FULL_DATA_SET_PATH) |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
print("finished") |