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Update get_started section in README #569

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1 change: 1 addition & 0 deletions CHANGELOG.md
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Expand Up @@ -45,6 +45,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
- Add logging to TSDataset.make_future, log repr of transform instead of class name ([#555](https://github.com/tinkoff-ai/etna/pull/555))
- Rename `_SARIMAXModel` and `_ProphetModel`, make `SARIMAXModel` and `ProphetModel` inherit from `PerSegmentPredictionIntervalModel` ([#549](https://github.com/tinkoff-ai/etna/pull/549))
-
- Update get_started section in README ([#569](https://github.com/tinkoff-ai/etna/pull/569))
- Make detrending polynomial ([#566](https://github.com/tinkoff-ai/etna/pull/566))
- Update documentation about transforms that generate regressors, update examples with them ([#572](https://github.com/tinkoff-ai/etna/pull/572))
-
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112 changes: 85 additions & 27 deletions README.md
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Expand Up @@ -42,7 +42,87 @@ The library started as an internal product in our company -
we use it in over 10+ projects now, so we often release updates.
Contributions are welcome - check our [Contribution Guide](https://github.com/tinkoff-ai/etna/blob/master/CONTRIBUTING.md).

## Get started

Let's load and prepare the data.
```python
import pandas as pd
from etna.datasets import TSDataset

# Read the data
df = pd.read_csv("examples/data/example_dataset.csv")

# Create a TSDataset
df = TSDataset.to_dataset(df)
ts = TSDataset(df, freq="D")

# Choose a horizon
HORIZON = 14

# Make train/test split
train_ts, test_ts = ts.train_test_split(test_size=HORIZON)
```

Define transformations and model:
```python
from etna.models import CatBoostModelMultiSegment
from etna.transforms import DateFlagsTransform
from etna.transforms import DensityOutliersTransform
from etna.transforms import FourierTransform
from etna.transforms import LagTransform
from etna.transforms import LinearTrendTransform
from etna.transforms import MeanTransform
from etna.transforms import SegmentEncoderTransform
from etna.transforms import TimeSeriesImputerTransform
from etna.transforms import TrendTransform

# Prepare transforms
transforms = [
DensityOutliersTransform(in_column="target", distance_coef=3.0),
TimeSeriesImputerTransform(in_column="target", strategy="forward_fill"),
LinearTrendTransform(in_column="target"),
TrendTransform(in_column="target", out_column="trend"),
LagTransform(in_column="target", lags=list(range(HORIZON, 122)), out_column="target_lag"),
DateFlagsTransform(week_number_in_month=True, out_column="date_flag"),
FourierTransform(period=360.25, order=6, out_column="fourier"),
SegmentEncoderTransform(),
MeanTransform(in_column=f"target_lag_{HORIZON}", window=12, seasonality=7),
MeanTransform(in_column=f"target_lag_{HORIZON}", window=7),
]

# Prepare model
model = CatBoostModelMultiSegment()
```

Fit `Pipeline` and make a prediction:
```python
from etna.pipeline import Pipeline

# Create and fit the pipeline
pipeline = Pipeline(model=model, transforms=transforms, horizon=HORIZON)
pipeline.fit(train_ts)

# Make a forecast
forecast_ts = pipeline.forecast()
```

Let's plot the results:
```python
from etna.analysis import plot_forecast

plot_forecast(forecast_ts=forecast_ts, test_ts=test_ts, train_ts=train_ts, n_train_samples=50)
```

![](examples/assets/readme/get_started.png)

Print the metric value across the segments:
```python
from etna.metrics import SMAPE

metric = SMAPE(mode="macro")
metric_value = metric(y_true=test_ts, y_pred=forecast_ts)
>>> {'segment_b': 3.3017151519000967, 'segment_c': 5.270557433427279, 'segment_a': 5.272811627335398, 'segment_d': 4.689085450895735}
```

## Installation

Expand Down Expand Up @@ -79,35 +159,10 @@ For example, `etna.models.ProphetModel` needs `prophet` extension and can't be u

ETNA supports configuration files. It means that library will check that all the specified packages are installed prior to script start and NOT during runtime.

To set up a configuration for your project you should create a `.etna` file at the project's root. To see the available options look at [`Settings`](https://github.com/tinkoff-ai/etna/blob/master/etna/settings.py#L68). There is an [example](https://github.com/tinkoff-ai/etna/tree/master/examples/configs/.etna) of configuration file.

## Get started
Here's some example code for a quick start.
```python
import pandas as pd
from etna.datasets.tsdataset import TSDataset
from etna.models import ProphetModel
from etna.pipeline import Pipeline

# Read the data
df = pd.read_csv("examples/data/example_dataset.csv")

# Create a TSDataset
df = TSDataset.to_dataset(df)
ts = TSDataset(df, freq="D")

# Choose a horizon
HORIZON = 8

# Fit the pipeline
pipeline = Pipeline(model=ProphetModel(), horizon=HORIZON)
pipeline.fit(ts)

# Make the forecast
forecast_ts = pipeline.forecast()
```
To set up a configuration for your project you should create a `.etna` file at the project's root. To see the available options look at [`Settings`](https://github.com/tinkoff-ai/etna/blob/master/etna/settings.py#L68). There is an [example](https://github.com/tinkoff-ai/etna/tree/master/examples/configs/.etna) of configuration file.

## Tutorials

We have also prepared a set of tutorials for an easy introduction:

| Notebook | Interactive launch |
Expand All @@ -121,6 +176,7 @@ We have also prepared a set of tutorials for an easy introduction:
| [Ensembles](https://github.com/tinkoff-ai/etna/tree/master/examples/ensembles.ipynb) | [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/tinkoff-ai/etna/master?filepath=examples/ensembles.ipynb) |

## Documentation

ETNA documentation is available [here](https://etna-docs.netlify.app/).

## Resources
Expand All @@ -134,6 +190,7 @@ ETNA documentation is available [here](https://etna-docs.netlify.app/).
## Acknowledgments

### ETNA.Team

[Andrey Alekseev](https://github.com/iKintosh),
[Nikita Barinov](https://github.com/diadorer),
[Dmitriy Bunin](https://github.com/Mr-Geekman),
Expand All @@ -148,6 +205,7 @@ ETNA documentation is available [here](https://etna-docs.netlify.app/).
[Julia Shenshina](https://github.com/julia-shenshina)

### ETNA.Contributors

[Artem Levashov](https://github.com/soft1q),
[Aleksey Podkidyshev](https://github.com/alekseyen),
[Carlosbogo](https://github.com/Carlosbogo)
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