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blue-yonder · Mar 11, 2024 · 4e4e42d · 4e4e42d
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diff --git a/AUTHORS.rst b/AUTHORS.rst
@@ -14,43 +14,91 @@ Core Development Team
 
 Contributions
 -------------
-- Markus Frey
-- Niklas Haas
-- earthgecko
-- Moritz Gelb
-- Thibault de Boissiere
+
+- Alan Larson
+- Alex Broekhof
+- Alex F
+- Alex Kennedy
+- Alex Loosley
+- Andrew Van Benschoten
+- Ben Auffarth
 - Brian Sang
-- Stephan Müller
-- Vin Tang
+- Brunno Vanelli
 - Chris Chow
-- Ezekiel Kruglick
-- Timo Klerx
-- Gregor Koehler
-- Matúš Tomlein
-- Florian Aspart
-- Sergey Shepelev
-- Justin White
-- J. Kleint
-- Marx
-- Delyan
-- Justin
-- Ricardo Emanuel Vaz Vargas
-- Roman Yurchak
-- Sergey Shepelev
-- Will Koehrsen
-- Wojciech Indyk
+- Chris Holdgraf
+- Christoph Hösler
 - cnzero
-- meer1992
-- supergitacc
-- Alex Loosley
 - CYHSM
-- Chris Holdgraf
 - Dan Mazur
+- Daniel Azevedo
 - Daniel Gomez
 - Daniel Naftalovich
+- Delyan
+- Denis Barbier
+- Derrick
+- Dhruv Srikanth
 - Dimitris Spathis
+- Dominic White
+- earthgecko
+- Emanuele Fumagalli
+- Erlend Aune
+- Evans Doe Ocansey
+- Ezekiel Kruglick
 - Filip Malkowski
+- filipj8
+- Florian Aspart
+- flyingdutchman23
+- Fujimoto Seiji
 - George Wambold
-- Brunno Vanelli
+- Greg Bodeker
+- Gregor Koehler
+- Gustavo Bertoli
+- Haris Sahovic
+- HaveF
+- He Kaisheng
+- Henry Swaffield
+- J. Kleint
+- James Myatt
+- Jean-Francois Zinque
+- Jeroen Van Der Donckt
+- Justin White
+- kartikey-vyas
+- koho
+- Lifepillar
+- lupupu
+- Mal Curtis
+- Mario Kahlhofer
+- Markus Frey
+- Marx
+- Matúš Tomlein
 - Maximilian Lohmann
+- meer1992
+- mendel5
+- Michele Tonutti
+- Moritz Gelb
+- Nigel Bosch
+- Niklas Haas
+- Oli
+- Omar Gutiérre
+- patrjon
+- Paul Fornia
 - Paul Voigt
+- Quan Gu
+- rhysimu
+- Ricardo Emanuel Vaz Vargas
+- Roman Yurchak
+- Roy Wedge
+- Sean M. Law
+- Sergey Shepelev
+- Soledad Galli
+- Stephan Müller
+- supergitacc
+- Tan Tao-Lin
+- Teo Bucci
+- Thibault Blanc
+- Thibault de Boissiere
+- Timo Klerx
+- Vincent Tang
+- Will Koehrsen
+- Wojciech Indyk
+- yairst
diff --git a/CHANGES.rst b/CHANGES.rst
@@ -4,6 +4,17 @@ Changelog
 
 tsfresh uses `Semantic Versioning <http://semver.org/>`_
 
+Version 0.20.2
+==============
+- Added Features
+ - Make Dask and Distributed optional dependencies (#1061)
+ - View and Set N Jobs (#1029)
+
+- Bugfixes/Typos/Documentation:
+ - Extra notes on parallelization efficiencies (#1046)
+ - Update doc extraction settings for clarity and formatting (#1033)
+ - Typos (#1031, #1034, #1049, #1048)
+
 Version 0.20.1
 ==============
 

diff --git a/docs/text/quick_start.rst b/docs/text/quick_start.rst
@@ -13,6 +13,15 @@ As the compiled tsfresh package is hosted on the Python Package Index (PyPI) you
 
  pip install tsfresh
 
+If you need to work with large time series data that may not fit in memory, install tsfresh with
+`Dask <https://www.dask.org>`_:
+
+.. code:: shell
+
+ pip install tsfresh[dask]
+
+See also :ref:`large-data-label`.
+
 
 Dive in
 -------

diff --git a/notebooks/05 Timeseries Forecasting.ipynb b/notebooks/05 Timeseries Forecasting.ipynb
@@ -215,7 +215,7 @@
  "cell_type": "markdown",
  "metadata": {},
  "source": [
- "we now have 1252 unique windows (identified by stock symbol and ending date):"
+ "we now have 1253 unique windows (identified by stock symbol and ending date):"
  ]
  },
  {
@@ -342,7 +342,7 @@
  "cell_type": "markdown",
  "metadata": {},
  "source": [
- "Just to repeat: the features in this row were only calculated using the time series values of `AAPL` up to and including `2015-07-14` and the last 20 days."
+ "Just to repeat: the features in this row were only calculated using the time series values of `AAPL` up to and including `2020-07-14` and the last 20 days."
  ]
  },
  {
@@ -418,7 +418,7 @@
  "source": [
  "We can now train normal AdaBoostRegressors to predict the next time step .\n",
  "Let's split the data into a training and testing sample (but make sure to keep temporal consistency).\n",
- "We take everything until 2019 as train data an the rest as test:"
+ "We take everything until 2020 as train data an the rest as test:"
  ]
  },
  {
@@ -427,7 +427,7 @@
  "metadata": {},
  "outputs": [],
  "source": [
- "X[:\"2018\"]"
+ "X[:\"2020\"]"
  ]
  },
  {
@@ -436,11 +436,11 @@
  "metadata": {},
  "outputs": [],
  "source": [
- "X_train = X[:\"2018\"]\n",
- "X_test = X[\"2019\":]\n",
+ "X_train = X[:\"2020\"]\n",
+ "X_test = X[\"2021\":]\n",
  "\n",
- "y_train = y[:\"2018\"]\n",
- "y_test = y[\"2019\":]"
+ "y_train = y[:\"2020\"]\n",
+ "y_test = y[\"2021\":]"
  ]
  },
  {
@@ -535,7 +535,7 @@
  "name": "python",
  "nbconvert_exporter": "python",
  "pygments_lexer": "ipython3",
- "version": "3.10.9"
+ "version": "3.10.13"
  }
  },
  "nbformat": 4,

diff --git a/notebooks/advanced/05 Timeseries Forecasting (multiple ids).ipynb b/notebooks/advanced/05 Timeseries Forecasting (multiple ids).ipynb
@@ -197,7 +197,7 @@
  "cell_type": "markdown",
  "metadata": {},
  "source": [
- "Just to repeat: the features in this row were only calculated using the time series values of `AAPL` up to and including `2015-07-15` and the last 20 days."
+ "Just to repeat: the features in this row were only calculated using the time series values of `AAPL` up to and including `2020-07-14` and the last 20 days."
  ]
  },
  {
@@ -268,11 +268,11 @@
  "metadata": {},
  "outputs": [],
  "source": [
- "X_train = X.loc[(slice(None), slice(None, \"2018\")), :]\n",
- "X_test = X.loc[(slice(None), slice(\"2019\", \"2020\")), :]\n",
+ "X_train = X.loc[(slice(None), slice(None, \"2020\")), :]\n",
+ "X_test = X.loc[(slice(None), slice(\"2021\", \"2022\")), :]\n",
  "\n",
- "y_train = y.loc[(slice(None), slice(None, \"2018\"))]\n",
- "y_test = y.loc[(slice(None), slice(\"2019\", \"2020\"))]"
+ "y_train = y.loc[(slice(None), slice(None, \"2020\"))]\n",
+ "y_test = y.loc[(slice(None), slice(\"2021\", \"2022\"))]"
  ]
  },
  {
@@ -336,6 +336,13 @@
  "y.unstack(\"Symbols\").plot(ax=plt.gca())\n",
  "y_pred.unstack(\"Symbols\").plot(ax=plt.gca(), legend=None, marker=\".\")"
  ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
  }
  ],
  "metadata": {
@@ -354,7 +361,7 @@
  "name": "python",
  "nbconvert_exporter": "python",
  "pygments_lexer": "ipython3",
- "version": "3.7.7"
+ "version": "3.10.13"
  }
  },
  "nbformat": 4,

diff --git a/notebooks/advanced/visualize-benjamini-yekutieli-procedure.ipynb b/notebooks/advanced/visualize-benjamini-yekutieli-procedure.ipynb
@@ -38,8 +38,7 @@
  "from tsfresh.feature_extraction import ComprehensiveFCParameters\n",
  "\n",
  "matplotlib.rcParams[\"figure.figsize\"] = [16, 6]\n",
- "matplotlib.rcParams[\"font.size\"] = 14\n",
- "matplotlib.style.use('seaborn-darkgrid')"
+ "matplotlib.rcParams[\"font.size\"] = 14"
  ]
  },
  {

diff --git a/setup.cfg b/setup.cfg
@@ -42,8 +42,6 @@ install_requires =
  patsy>=0.4.1
  scikit-learn>=0.22.0
  tqdm>=4.10.0
- dask[dataframe]>=2.9.0
- distributed>=2.11.0
  stumpy>=1.7.2
  cloudpickle
 
@@ -56,6 +54,9 @@ exclude =
  tests*
 
 [options.extras_require]
+dask =
+ dask[dataframe]>=2.9.0
+ distributed>=2.11.0
 matrixprofile =
  matrixprofile>=1.1.10,<2.0.0
 
@@ -67,6 +68,7 @@ docs =
 
 # Add here test requirements (semicolon/line-separated)
 testing =
+ %(dask)s
  pytest>=4.4.0
  pytest-cov>=2.6.1
  pytest-xdist>=1.26.1