Giới thiệu chuỗi thời gian
Phát hiện bất thường với Python
Bekhruz (Bex) Tuychiev
Kaggle Master, Data Science Content Creator
Bộ dữ liệu cổ phiếu Google
import pandas as pd
google = pd.read_csv("google.csv")
google.head()
Open High Low Close Volume
Date
2006-01-03 211.47 218.05 209.32 217.83 13137450
2006-01-04 222.17 224.70 220.09 222.84 15292353
2006-01-05 223.22 226.00 220.97 225.85 10815661
2006-01-06 228.66 235.49 226.85 233.06 17759521
2006-01-09 233.44 236.94 230.70 233.68 12795837
Kiểu dữ liệu DateTime
print(google['Date'].dtype)
object
google['Date'] = pd.to_datetime(google['Date'])
print(google.dtypes)
Date datetime64[ns]
Open float64
High float64
...
Trích xuất đặc trưng
google['day_of_week'] = google['Date'].dt.day_of_week google['day_of_month'] = google['Date'].dt.day google['month'] = google['Date'].dt.monthgoogle.sample(5)
Date Open Low Close Volume day_of_week month day_of_month
2016-02-29 721.00 716.84 717.22 2237474 0 2 29
2007-01-24 242.46 241.89 249.78 6074077 2 1 24
2007-05-24 237.81 235.99 237.40 4200474 3 5 24
2008-09-16 213.19 212.96 221.69 6991767 1 9 16
2008-03-31 218.04 216.22 220.46 4446368 0 3 31
DatetimeIndex
google.set_index("Date", inplace=True)
google.head()
Open High Low Close Volume day_of_week month \
Date
2006-01-03 211.47 218.05 209.32 217.83 13137450 1 1
2006-01-04 222.17 224.70 220.09 222.84 15292353 2 1
2006-01-05 223.22 226.00 220.97 225.85 10815661 3 1
2006-01-06 228.66 235.49 226.85 233.06 17759521 4 1
2006-01-09 233.44 236.94 230.70 233.68 12795837 0 1
Chọn khoảng thời gian
google["2008": "2010"].head()
Open High Low Close Volume day_of_week month \
Date
2008-01-02 346.78 349.03 339.20 342.94 4306848 2 1
2008-01-03 342.97 343.77 338.60 343.01 3252846 3 1
2008-01-04 340.18 340.82 327.83 328.83 5359834 4 1
2008-01-07 327.30 331.47 318.99 324.95 6404945 0 1
2008-01-08 326.83 330.31 315.82 316.16 5341949 1 1
Chọn khoảng thời gian
google["2012-03": "2015-10-04"].head()
Open High Low Close Volume day_of_week month \
Date
2012-03-01 311.44 313.16 309.38 311.51 2238010 3 3
2012-03-02 311.31 312.31 310.47 310.94 1573214 4 3
2012-03-05 310.53 311.56 306.00 307.43 1593250 0 3
2012-03-06 304.33 304.71 297.22 302.78 3175216 1 3
2012-03-07 304.83 305.90 303.23 303.70 1264892 2 3
Nạp dữ liệu với DatetimeIndex
google = pd.read_csv("google.csv", parse_dates=["Date"], index_col="Date")
google.head()
Open High Low Close Volume
Date
2006-01-03 211.47 218.05 209.32 217.83 13137450
2006-01-04 222.17 224.70 220.09 222.84 15292353
2006-01-05 223.22 226.00 220.97 225.85 10815661
2006-01-06 228.66 235.49 226.85 233.06 17759521
2006-01-09 233.44 236.94 230.70 233.68 12795837
Vẽ chuỗi thời gian
import matplotlib.pyplot as plt
google["Close"].plot(color="red")
plt.title("""Giá đóng cửa cổ phiếu Google
2006–2018.""")
plt.show()
Vẽ chuỗi thời gian
google["2010": "2010-07-01"]['Close'].plot(color="green")
plt.title("Giá đóng cửa Google từ 01/2010 đến 07/2010.")
plt.show()
Vẽ chuỗi thời gian
google['Volume'].plot(color='red', figsize=(12, 4))
plt.title("Số cổ phiếu Google được giao dịch 2006–2018.")
MAD cho chuỗi thời gian
from pyod.models.mad import MAD mad = MAD().fit(google[['Volume']])is_outlier = mad.labels_ == 1 print(len(google[is_outlier]))
236
IForest cho chuỗi thời gian
google['day_of_week'] = google.index.day_of_week
google['month'] = google.index.month
google['day_of_month'] = google.index.day
google.head()
Open High Low Close Volume day_of_week month \
Date
2006-01-03 211.47 218.05 209.32 217.83 13137450 1 1
2006-01-04 222.17 224.70 220.09 222.84 15292353 2 1
2006-01-05 223.22 226.00 220.97 225.85 10815661 3 1
2006-01-06 228.66 235.49 226.85 233.06 17759521 4 1
2006-01-09 233.44 236.94 230.70 233.68 12795837 0 1
IForest cho chuỗi thời gian
from pyod.models.iforest import IForest iforest = IForest().fit(google)# Generate probabilities probs = iforest.predict_proba(google) # Isolate the outliers is_outlier = probs[:, 1] > 0.75 outliers = google[is_outlier] print(len(outliers))
60
Ayo berlatih!
Phát hiện bất thường với Python
