File size: 1,820 Bytes
40e52c6 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 | import pandas as pd
print("cargar data")
# Login using e.g. `huggingface-cli login` to access this dataset
df = pd.read_csv("hf://datasets/erickfmm/Tesis_UChile/train.csv", encoding="utf-8")
print("data cargada")
final_data = {}
total = len(df)
for idx, row in df.iterrows():
#print(idx, row)
final_data[row["origen"]] = {"_id": row["origen"]} if row["origen"] not in final_data else final_data[row["origen"]]
valor = row["value"] if not pd.isna(row["value"]) or row["value"] is not None else None
if valor is None:
continue
lang = row["lang"] if not pd.isna(row["lang"]) else None
valor = {"value": valor}
if lang is not None:
valor["lang"] = lang
if pd.isna(row["DC"]) and row["nombre"] == "filelink":
row["DC"] = "extra.file.link"
if row["DC"] not in final_data[row["origen"]]:
final_data[row["origen"]][row["DC"]] = valor
else:
if type(final_data[row["origen"]][row["DC"]]) is list:
final_data[row["origen"]][row["DC"]].append(valor)
else:
final_data[row["origen"]][row["DC"]] = [final_data[row["origen"]][row["DC"]], valor]
if idx % 10000 == 0:
print("procesados ", idx)
print(idx/float(total)*100.0, "%")
#import pprint
#pprint.pprint(final_data, indent=2)
import json
#print(json.dumps(final_data, indent=2))
print("save pretty")
json.dump([final_data[idx] for idx in final_data.keys()], open("tesis_uchile_pretty.json", "w", encoding="utf-8"), indent=2, ensure_ascii=False)
print("save min")
json.dump([final_data[idx] for idx in final_data.keys()], open("tesis_uchile_min.json", "w", encoding="utf-8"), ensure_ascii=False)
print("save jsonl")
with open("tesis.uchile.jsonl", "w", encoding="utf-8") as fh:
for idx in final_data.keys():
json.dump(final_data[idx], fh, ensure_ascii=False)
fh.write("\n")
fh.flush()
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