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poetry.lock
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poetry.lock
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[[package]]
category = "main"
description = "Composable style cycles"
name = "cycler"
optional = false
python-versions = "*"
version = "0.10.0"
[package.dependencies]
six = "*"
[[package]]
category = "main"
description = "A fast implementation of the Cassowary constraint solver"
name = "kiwisolver"
optional = false
python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
version = "1.1.0"
[package.dependencies]
setuptools = "*"
[[package]]
category = "main"
description = "Python plotting package"
name = "matplotlib"
optional = false
python-versions = ">=3.6"
version = "3.1.2"
[package.dependencies]
cycler = ">=0.10"
kiwisolver = ">=1.0.1"
numpy = ">=1.11"
pyparsing = ">=2.0.1,<2.0.4 || >2.0.4,<2.1.2 || >2.1.2,<2.1.6 || >2.1.6"
python-dateutil = ">=2.1"
[[package]]
category = "main"
description = "NumPy is the fundamental package for array computing with Python."
name = "numpy"
optional = false
python-versions = ">=3.5"
version = "1.18.1"
[[package]]
category = "main"
description = "Powerful data structures for data analysis, time series, and statistics"
name = "pandas"
optional = false
python-versions = ">=3.5.3"
version = "0.25.3"
[package.dependencies]
numpy = ">=1.13.3"
python-dateutil = ">=2.6.1"
pytz = ">=2017.2"
[[package]]
category = "main"
description = "Python parsing module"
name = "pyparsing"
optional = false
python-versions = ">=2.6, !=3.0.*, !=3.1.*, !=3.2.*"
version = "2.4.6"
[[package]]
category = "main"
description = "Extensions to the standard Python datetime module"
name = "python-dateutil"
optional = false
python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,>=2.7"
version = "2.8.1"
[package.dependencies]
six = ">=1.5"
[[package]]
category = "main"
description = "World timezone definitions, modern and historical"
name = "pytz"
optional = false
python-versions = "*"
version = "2019.3"
[[package]]
category = "main"
description = "SciPy: Scientific Library for Python"
name = "scipy"
optional = false
python-versions = ">=3.5"
version = "1.4.1"
[package.dependencies]
numpy = ">=1.13.3"
[[package]]
category = "main"
description = "seaborn: statistical data visualization"
name = "seaborn"
optional = false
python-versions = ">=3.6"
version = "0.10.0"
[package.dependencies]
matplotlib = ">=2.1.2"
numpy = ">=1.13.3"
pandas = ">=0.22.0"
scipy = ">=1.0.1"
[[package]]
category = "main"
description = "Python 2 and 3 compatibility utilities"
name = "six"
optional = false
python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*"
version = "1.14.0"
[metadata]
content-hash = "270a2ba416aaa0825860c91416b5f4a1250f937964cc7b3cb11310e2875e701f"
python-versions = "^3.7"
[metadata.hashes]
cycler = ["1d8a5ae1ff6c5cf9b93e8811e581232ad8920aeec647c37316ceac982b08cb2d", "cd7b2d1018258d7247a71425e9f26463dfb444d411c39569972f4ce586b0c9d8"]
kiwisolver = ["05b5b061e09f60f56244adc885c4a7867da25ca387376b02c1efc29cc16bcd0f", "26f4fbd6f5e1dabff70a9ba0d2c4bd30761086454aa30dddc5b52764ee4852b7", "3b2378ad387f49cbb328205bda569b9f87288d6bc1bf4cd683c34523a2341efe", "400599c0fe58d21522cae0e8b22318e09d9729451b17ee61ba8e1e7c0346565c", "47b8cb81a7d18dbaf4fed6a61c3cecdb5adec7b4ac292bddb0d016d57e8507d5", "53eaed412477c836e1b9522c19858a8557d6e595077830146182225613b11a75", "58e626e1f7dfbb620d08d457325a4cdac65d1809680009f46bf41eaf74ad0187", "5a52e1b006bfa5be04fe4debbcdd2688432a9af4b207a3f429c74ad625022641", "5c7ca4e449ac9f99b3b9d4693debb1d6d237d1542dd6a56b3305fe8a9620f883", "682e54f0ce8f45981878756d7203fd01e188cc6c8b2c5e2cf03675390b4534d5", "79bfb2f0bd7cbf9ea256612c9523367e5ec51d7cd616ae20ca2c90f575d839a2", "7f4dd50874177d2bb060d74769210f3bce1af87a8c7cf5b37d032ebf94f0aca3", "8944a16020c07b682df861207b7e0efcd2f46c7488619cb55f65882279119389", "8aa7009437640beb2768bfd06da049bad0df85f47ff18426261acecd1cf00897", "939f36f21a8c571686eb491acfffa9c7f1ac345087281b412d63ea39ca14ec4a", "9733b7f64bd9f807832d673355f79703f81f0b3e52bfce420fc00d8cb28c6a6c", "a02f6c3e229d0b7220bd74600e9351e18bc0c361b05f29adae0d10599ae0e326", "a0c0a9f06872330d0dd31b45607197caab3c22777600e88031bfe66799e70bb0", "acc4df99308111585121db217681f1ce0eecb48d3a828a2f9bbf9773f4937e9e", "b64916959e4ae0ac78af7c3e8cef4becee0c0e9694ad477b4c6b3a536de6a544", "d3fcf0819dc3fea58be1fd1ca390851bdb719a549850e708ed858503ff25d995", "d52e3b1868a4e8fd18b5cb15055c76820df514e26aa84cc02f593d99fef6707f", "db1a5d3cc4ae943d674718d6c47d2d82488ddd94b93b9e12d24aabdbfe48caee", "e3a21a720791712ed721c7b95d433e036134de6f18c77dbe96119eaf7aa08004", "e8bf074363ce2babeb4764d94f8e65efd22e6a7c74860a4f05a6947afc020ff2", "f16814a4a96dc04bf1da7d53ee8d5b1d6decfc1a92a63349bb15d37b6a263dd9", "f2b22153870ca5cf2ab9c940d7bc38e8e9089fa0f7e5856ea195e1cf4ff43d5a", "f790f8b3dff3d53453de6a7b7ddd173d2e020fb160baff578d578065b108a05f"]
matplotlib = ["08ccc8922eb4792b91c652d3e6d46b1c99073f1284d1b6705155643e8046463a", "161dcd807c0c3232f4dcd4a12a382d52004a498174cbfafd40646106c5bcdcc8", "1f9e885bfa1b148d16f82a6672d043ecf11197f6c71ae222d0546db706e52eb2", "2d6ab54015a7c0d727c33e36f85f5c5e4172059efdd067f7527f6e5d16ad01aa", "5d2e408a2813abf664bd79431107543ecb449136912eb55bb312317edecf597e", "61c8b740a008218eb604de518eb411c4953db0cb725dd0b32adf8a81771cab9e", "80f10af8378fccc136da40ea6aa4a920767476cdfb3241acb93ef4f0465dbf57", "819d4860315468b482f38f1afe45a5437f60f03eaede495d5ff89f2eeac89500", "8cc0e44905c2c8fda5637cad6f311eb9517017515a034247ab93d0cf99f8bb7a", "8e8e2c2fe3d873108735c6ee9884e6f36f467df4a143136209cff303b183bada", "98c2ffeab8b79a4e3a0af5dd9939f92980eb6e3fec10f7f313df5f35a84dacab", "d59bb0e82002ac49f4152963f8a1079e66794a4f454457fd2f0dcc7bf0797d30", "ee59b7bb9eb75932fe3787e54e61c99b628155b0cedc907864f24723ba55b309"]
numpy = ["1786a08236f2c92ae0e70423c45e1e62788ed33028f94ca99c4df03f5be6b3c6", "17aa7a81fe7599a10f2b7d95856dc5cf84a4eefa45bc96123cbbc3ebc568994e", "20b26aaa5b3da029942cdcce719b363dbe58696ad182aff0e5dcb1687ec946dc", "2d75908ab3ced4223ccba595b48e538afa5ecc37405923d1fea6906d7c3a50bc", "39d2c685af15d3ce682c99ce5925cc66efc824652e10990d2462dfe9b8918c6a", "56bc8ded6fcd9adea90f65377438f9fea8c05fcf7c5ba766bef258d0da1554aa", "590355aeade1a2eaba17617c19edccb7db8d78760175256e3cf94590a1a964f3", "70a840a26f4e61defa7bdf811d7498a284ced303dfbc35acb7be12a39b2aa121", "77c3bfe65d8560487052ad55c6998a04b654c2fbc36d546aef2b2e511e760971", "9537eecf179f566fd1c160a2e912ca0b8e02d773af0a7a1120ad4f7507cd0d26", "9acdf933c1fd263c513a2df3dceecea6f3ff4419d80bf238510976bf9bcb26cd", "ae0975f42ab1f28364dcda3dde3cf6c1ddab3e1d4b2909da0cb0191fa9ca0480", "b3af02ecc999c8003e538e60c89a2b37646b39b688d4e44d7373e11c2debabec", "b6ff59cee96b454516e47e7721098e6ceebef435e3e21ac2d6c3b8b02628eb77", "b765ed3930b92812aa698a455847141869ef755a87e099fddd4ccf9d81fffb57", "c98c5ffd7d41611407a1103ae11c8b634ad6a43606eca3e2a5a269e5d6e8eb07", "cf7eb6b1025d3e169989416b1adcd676624c2dbed9e3bcb7137f51bfc8cc2572", "d92350c22b150c1cae7ebb0ee8b5670cc84848f6359cf6b5d8f86617098a9b73", "e422c3152921cece8b6a2fb6b0b4d73b6579bd20ae075e7d15143e711f3ca2ca", "e840f552a509e3380b0f0ec977e8124d0dc34dc0e68289ca28f4d7c1d0d79474", "f3d0a94ad151870978fb93538e95411c83899c9dc63e6fb65542f769568ecfa5"]
pandas = ["00dff3a8e337f5ed7ad295d98a31821d3d0fe7792da82d78d7fd79b89c03ea9d", "22361b1597c8c2ffd697aa9bf85423afa9e1fcfa6b1ea821054a244d5f24d75e", "255920e63850dc512ce356233081098554d641ba99c3767dde9e9f35630f994b", "26382aab9c119735908d94d2c5c08020a4a0a82969b7e5eefb92f902b3b30ad7", "33970f4cacdd9a0ddb8f21e151bfb9f178afb7c36eb7c25b9094c02876f385c2", "4545467a637e0e1393f7d05d61dace89689ad6d6f66f267f86fff737b702cce9", "52da74df8a9c9a103af0a72c9d5fdc8e0183a90884278db7f386b5692a2220a4", "61741f5aeb252f39c3031d11405305b6d10ce663c53bc3112705d7ad66c013d0", "6a3ac2c87e4e32a969921d1428525f09462770c349147aa8e9ab95f88c71ec71", "7458c48e3d15b8aaa7d575be60e1e4dd70348efcd9376656b72fecd55c59a4c3", "78bf638993219311377ce9836b3dc05f627a666d0dbc8cec37c0ff3c9ada673b", "8153705d6545fd9eb6dd2bc79301bff08825d2e2f716d5dced48daafc2d0b81f", "975c461accd14e89d71772e89108a050fa824c0b87a67d34cedf245f6681fc17", "9962957a27bfb70ab64103d0a7b42fa59c642fb4ed4cb75d0227b7bb9228535d", "adc3d3a3f9e59a38d923e90e20c4922fc62d1e5a03d083440468c6d8f3f1ae0a", "bbe3eb765a0b1e578833d243e2814b60c825b7fdbf4cdfe8e8aae8a08ed56ecf", "df8864824b1fe488cf778c3650ee59c3a0d8f42e53707de167ba6b4f7d35f133", "e45055c30a608076e31a9fcd780a956ed3b1fa20db61561b8d88b79259f526f7", "ee50c2142cdcf41995655d499a157d0a812fce55c97d9aad13bc1eef837ed36c"]
pyparsing = ["4c830582a84fb022400b85429791bc551f1f4871c33f23e44f353119e92f969f", "c342dccb5250c08d45fd6f8b4a559613ca603b57498511740e65cd11a2e7dcec"]
python-dateutil = ["73ebfe9dbf22e832286dafa60473e4cd239f8592f699aa5adaf10050e6e1823c", "75bb3f31ea686f1197762692a9ee6a7550b59fc6ca3a1f4b5d7e32fb98e2da2a"]
pytz = ["1c557d7d0e871de1f5ccd5833f60fb2550652da6be2693c1e02300743d21500d", "b02c06db6cf09c12dd25137e563b31700d3b80fcc4ad23abb7a315f2789819be"]
scipy = ["00af72998a46c25bdb5824d2b729e7dabec0c765f9deb0b504f928591f5ff9d4", "0902a620a381f101e184a958459b36d3ee50f5effd186db76e131cbefcbb96f7", "1e3190466d669d658233e8a583b854f6386dd62d655539b77b3fa25bfb2abb70", "2cce3f9847a1a51019e8c5b47620da93950e58ebc611f13e0d11f4980ca5fecb", "3092857f36b690a321a662fe5496cb816a7f4eecd875e1d36793d92d3f884073", "386086e2972ed2db17cebf88610aab7d7f6e2c0ca30042dc9a89cf18dcc363fa", "71eb180f22c49066f25d6df16f8709f215723317cc951d99e54dc88020ea57be", "770254a280d741dd3436919d47e35712fb081a6ff8bafc0f319382b954b77802", "787cc50cab3020a865640aba3485e9fbd161d4d3b0d03a967df1a2881320512d", "8a07760d5c7f3a92e440ad3aedcc98891e915ce857664282ae3c0220f3301eb6", "8d3bc3993b8e4be7eade6dcc6fd59a412d96d3a33fa42b0fa45dc9e24495ede9", "9508a7c628a165c2c835f2497837bf6ac80eb25291055f56c129df3c943cbaf8", "a144811318853a23d32a07bc7fd5561ff0cac5da643d96ed94a4ffe967d89672", "a1aae70d52d0b074d8121333bc807a485f9f1e6a69742010b33780df2e60cfe0", "a2d6df9eb074af7f08866598e4ef068a2b310d98f87dc23bd1b90ec7bdcec802", "bb517872058a1f087c4528e7429b4a44533a902644987e7b2fe35ecc223bc408", "c5cac0c0387272ee0e789e94a570ac51deb01c796b37fb2aad1fb13f85e2f97d", "cc971a82ea1170e677443108703a2ec9ff0f70752258d0e9f5433d00dda01f59", "dba8306f6da99e37ea08c08fef6e274b5bf8567bb094d1dbe86a20e532aca088", "dc60bb302f48acf6da8ca4444cfa17d52c63c5415302a9ee77b3b21618090521", "dee1bbf3a6c8f73b6b218cb28eed8dd13347ea2f87d572ce19b289d6fd3fbc59"]
seaborn = ["59fe414e138d7d5ea08b0feb01b86caf4682e36fa748e3987730523a89aecbb9", "bdf7714ef7d4603e6325d3902e80a46d6149561e1cc237ac08a1c05c3f55a996"]
six = ["236bdbdce46e6e6a3d61a337c0f8b763ca1e8717c03b369e87a7ec7ce1319c0a", "8f3cd2e254d8f793e7f3d6d9df77b92252b52637291d0f0da013c76ea2724b6c"]