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45 lines
1.0 KiB
Python
45 lines
1.0 KiB
Python
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import pandas as pd
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import torch
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import os
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import numpy as np
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def clean_volume_0(df):
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# null replace to 0
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df = df.replace(np.nan, 0)
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df = df.replace(np.inf, 0)
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df = df.fillna(0)
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df["volume"] = df["volume"].astype(int)
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index = df.loc[df["volume"] == 0].index
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df = df.drop(df.index[index])
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index = df.loc[df["close"] == 0].index
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df = df.drop(df.index[index])
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df.reset_index(drop=True)
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return df
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def process_features(in_dir, out_dir):
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# codes = pd.read_csv("./datasets/all_codes.csv")
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# codes = codes["code"].tolist()
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# codes = ["sz.300001"]
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file_dir = in_dir # "./datasets/origins"
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a_s = [a for a in sorted(os.listdir(file_dir), key=lambda x: str(x[5:]))]
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for a in a_s:
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file = os.path.join(file_dir, a)
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df = pd.read_csv(file)
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df = clean_volume_0(df)
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df.to_csv(os.path.join(out_dir, a))
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print(a)
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process_features(in_dir="./datasets/cyday", out_dir="./datasets/cleaned/")
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