Merge pull request #335 from unit8co/feature/fix-notebooks

fix datasets usage in notebooks

Author: hrzn

examples/01-darts-intro.ipynb

@@ -107,7 +107,7 @@
     }
    ],
    "source": [
-    "series = AirPassengersDataset.load()\n",
+    "series = AirPassengersDataset().load()\n",
     "series.plot()"
    ]
   },
@@ -1134,7 +1134,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.10"
+   "version": "3.8.5"
   },
   "pycharm": {
    "stem_cell": {

examples/02-multi-time-series-and-covariates.ipynb

@@ -65,8 +65,8 @@
     }
    ],
    "source": [
-    "series_air = AirPassengersDataset.load()\n",
-    "series_milk = MonthlyMilkDataset.load()\n",
+    "series_air = AirPassengersDataset().load()\n",
+    "series_milk = MonthlyMilkDataset().load()\n",
     "\n",
     "series_air.plot(label='Number of air passengers')\n",
     "series_milk.plot(label='Pounds of milk produced per cow')\n",
@@ -757,7 +757,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.13"
+   "version": "3.8.5"
   }
  },
  "nbformat": 4,

examples/03-data-processing.ipynb

@@ -126,7 +126,7 @@
     }
    ],
    "source": [
-    "series = MonthlyMilkDataset.load()\n",
+    "series = MonthlyMilkDataset().load()\n",
     "\n",
     "print(series)\n",
     "series.plot()"
@@ -250,7 +250,7 @@
     }
    ],
    "source": [
-    "incomplete_series = MonthlyMilkIncompleteDataset.load()\n",
+    "incomplete_series = MonthlyMilkIncompleteDataset().load()\n",
     "incomplete_series.plot()\n"
    ]
   },
@@ -624,7 +624,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "incomplete_series = MonthlyMilkIncompleteDataset.load()\n",
+    "incomplete_series = MonthlyMilkIncompleteDataset().load()\n",
     "\n",
     "filler = MissingValuesFiller()\n",
     "scaler = Scaler()\n",
@@ -679,8 +679,8 @@
     }
    ],
    "source": [
-    "series = MonthlyMilkDataset.load()\n",
-    "incomplete_series = MonthlyMilkIncompleteDataset.load()\n",
+    "series = MonthlyMilkDataset().load()\n",
+    "incomplete_series = MonthlyMilkIncompleteDataset().load()\n",
     "\n",
     "multiple_ts = [incomplete_series, series[:10]]\n",
     "\n",
@@ -764,7 +764,7 @@
     }
    ],
    "source": [
-    "series = MonthlyMilkIncompleteDataset.load()\n",
+    "series = MonthlyMilkIncompleteDataset().load()\n",
     "\n",
     "huge_number_of_series = [series]*100000\n",
     "\n",
@@ -840,7 +840,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.13"
+   "version": "3.8.5"
   }
  },
  "nbformat": 4,

examples/04-FFT-examples.ipynb

@@ -73,7 +73,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "ts = TemperatureDataset.load()"
+    "ts = TemperatureDataset().load()"
    ]
   },
   {
@@ -417,7 +417,7 @@
     }
    ],
    "source": [
-    "ts_2 = AirPassengersDataset.load()\n",
+    "ts_2 = AirPassengersDataset().load()\n",
     "train, val = ts_2.split_after(pd.Timestamp('19551201'))\n",
     "train.plot()\n",
     "val.plot()"
@@ -542,7 +542,7 @@
     }
    ],
    "source": [
-    "ts_3 = EnergyDataset.load()\n",
+    "ts_3 = EnergyDataset().load()\n",
     "ts_3 = fill_missing_values(ts_3, 'auto')\n",
     "ts_3 = ts_3['generation nuclear']\n",
     "train, val = ts_3.split_after(pd.Timestamp('2017-07-01'))\n",
@@ -609,7 +609,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.8"
+   "version": "3.8.5"
   }
  },
  "nbformat": 4,

examples/05-RNN-examples.ipynb

@@ -78,7 +78,7 @@
    "outputs": [],
    "source": [
     "# Read data:\n",
-    "series = AirPassengersDataset.load()\n",
+    "series = AirPassengersDataset().load()\n",
     "\n",
     "# Create training and validation sets:\n",
     "train, val = series.split_after(pd.Timestamp('19590101'))\n",
@@ -476,7 +476,7 @@
     }
    ],
    "source": [
-    "series_sunspot = SunspotsDataset.load()\n",
+    "series_sunspot = SunspotsDataset().load()\n",
     "\n",
     "series_sunspot.plot()\n",
     "check_seasonality(series_sunspot, max_lag=240)"
@@ -693,7 +693,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.13"
+   "version": "3.8.5"
   }
  },
  "nbformat": 4,

examples/06-TCN-examples.ipynb

@@ -60,7 +60,7 @@
    "outputs": [],
    "source": [
     "# Read data:\n",
-    "ts = AirPassengersDataset.load()\n",
+    "ts = AirPassengersDataset().load()\n",
     "scaler = Scaler()\n",
     "ts = scaler.fit_transform(ts)  # scale the whole time series not caring about train/val split...\n",
     "\n",
@@ -210,7 +210,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "series_sunspot = SunspotsDataset.load()\n",
+    "series_sunspot = SunspotsDataset().load()\n",
     "scaler = Scaler()\n",
     "series_sp_transformed = scaler.fit_transform(series_sunspot)\n",
     "\n",
@@ -350,7 +350,7 @@
     }
    ],
    "source": [
-    "df3 = EnergyDataset.load().pd_data_frame()\n",
+    "df3 = EnergyDataset().load().pd_data_frame()\n",
     "df3_day_avg = df3.groupby(df3['time'].astype(str).str.split(\" \").str[0]).mean().reset_index()\n",
     "series_en = fill_missing_values(TimeSeries.from_dataframe(df3_day_avg, 'time', ['generation hydro run-of-river and poundage']), 'auto')\n",
     "\n",
@@ -495,7 +495,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.13"
+   "version": "3.8.5"
   }
  },
  "nbformat": 4,

examples/07-Transformer-examples.ipynb

@@ -85,7 +85,7 @@
    "outputs": [],
    "source": [
     "# Read data:\n",
-    "series = AirPassengersDataset.load()\n",
+    "series = AirPassengersDataset().load()\n",
     "\n",
     "# Create training and validation sets:\n",
     "train, val = series.split_after(pd.Timestamp('19590101'))\n",
@@ -390,7 +390,7 @@
     }
    ],
    "source": [
-    "series_sunspot = SunspotsDataset.load()\n",
+    "series_sunspot = SunspotsDataset().load()\n",
     "\n",
     "series_sunspot.plot()\n",
     "check_seasonality(series_sunspot, max_lag=240)\n",
@@ -607,7 +607,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.13"
+   "version": "3.8.5"
   }
  },
  "nbformat": 4,

examples/08-NBEATS-examples.ipynb

@@ -95,7 +95,7 @@
     }
    ],
    "source": [
-    "df = EnergyDataset.load().pd_dataframe()\n",
+    "df = EnergyDataset().load().pd_dataframe()\n",
     "df['generation hydro run-of-river and poundage'].plot()\n",
     "plt.title('Hourly generation hydro run-of-river and poundage');"
    ]
@@ -458,7 +458,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.8"
+   "version": "3.8.5"
   }
  },
  "nbformat": 4,