Merge remote-tracking branch 'upstream/master' into ArrowStringArray.astype

Author: simonjayhawkins

.github/workflows/ci.yml

@@ -22,7 +22,9 @@ jobs:
 
  steps:
  - name: Checkout
- uses: actions/checkout@v1
+ uses: actions/checkout@v2
+ with:
+ fetch-depth: 0
 
  - name: Looking for unwanted patterns
  run: ci/code_checks.sh patterns
@@ -94,7 +96,9 @@ jobs:
  steps:
 
  - name: Checkout
- uses: actions/checkout@v1
+ uses: actions/checkout@v2
+ with:
+ fetch-depth: 0
 
  - name: Set up pandas
  uses: ./.github/actions/setup
@@ -147,7 +151,9 @@ jobs:
  steps:
 
  - name: Checkout
- uses: actions/checkout@v1
+ uses: actions/checkout@v2
+ with:
+ fetch-depth: 0
 
  - name: Set up pandas
  uses: ./.github/actions/setup

.github/workflows/database.yml

@@ -56,10 +56,12 @@ jobs:
 
  steps:
  - name: Checkout
- uses: actions/checkout@v1
+ uses: actions/checkout@v2
+ with:
+ fetch-depth: 0
 
  - name: Cache conda
- uses: actions/cache@v1
+ uses: actions/cache@v2
  env:
  CACHE_NUMBER: 0
  with:
@@ -70,7 +72,7 @@ jobs:
  - uses: conda-incubator/setup-miniconda@v2
  with:
  activate-environment: pandas-dev
- channel-priority: strict
+ channel-priority: flexible
  environment-file: ${{ matrix.ENV_FILE }}
  use-only-tar-bz2: true
 

.github/workflows/posix.yml

@@ -44,10 +44,12 @@ jobs:
 
  steps:
  - name: Checkout
- uses: actions/checkout@v1
+ uses: actions/checkout@v2
+ with:
+ fetch-depth: 0
 
  - name: Cache conda
- uses: actions/cache@v1
+ uses: actions/cache@v2
  env:
  CACHE_NUMBER: 0
  with:

.pre-commit-config.yaml

@@ -19,13 +19,14 @@ repos:
  types_or: [python, rst, markdown]
  files: ^(pandas|doc)/
 - repo: https://github.com/pre-commit/pre-commit-hooks
- rev: v3.4.0
+ rev: v4.0.1
  hooks:
+ - id: debug-statements
  - id: end-of-file-fixer
  exclude: \.txt$
  - id: trailing-whitespace
 - repo: https://github.com/cpplint/cpplint
- rev: f7061b1 # the latest tag does not have the hook
+ rev: 1.5.5
  hooks:
  - id: cpplint
  # We don't lint all C files because we don't want to lint any that are built
@@ -35,7 +36,7 @@ repos:
  exclude: ^pandas/_libs/src/(klib|headers)/
  args: [--quiet, '--extensions=c,h', '--headers=h', --recursive, '--filter=-readability/casting,-runtime/int,-build/include_subdir']
 - repo: https://gitlab.com/pycqa/flake8
- rev: 3.9.1
+ rev: 3.9.2
  hooks:
  - id: flake8
  additional_dependencies:
@@ -56,7 +57,7 @@ repos:
  hooks:
  - id: isort
 - repo: https://github.com/asottile/pyupgrade
- rev: v2.12.0
+ rev: v2.18.3
  hooks:
  - id: pyupgrade
  args: [--py37-plus]
@@ -71,11 +72,11 @@ repos:
  types: [text] # overwrite types: [rst]
  types_or: [python, rst]
 - repo: https://github.com/asottile/yesqa
- rev: v1.2.2
+ rev: v1.2.3
  hooks:
  - id: yesqa
  additional_dependencies:
- - flake8==3.9.1
+ - flake8==3.9.2
  - flake8-comprehensions==3.1.0
  - flake8-bugbear==21.3.2
  - pandas-dev-flaker==0.2.0

.travis.yml

@@ -45,7 +45,6 @@ before_install:
  - echo "before_install"
  # Use blocking IO on travis. Ref: https://github.com/travis-ci/travis-ci/issues/8920#issuecomment-352661024
  - python -c 'import os,sys,fcntl; flags = fcntl.fcntl(sys.stdout, fcntl.F_GETFL); fcntl.fcntl(sys.stdout, fcntl.F_SETFL, flags&~os.O_NONBLOCK);'
- - source ci/travis_process_gbq_encryption.sh
  - export PATH="$HOME/miniconda3/bin:$PATH"
  - df -h
  - pwd

LICENSES/PACKAGING_LICENSE

@@ -0,0 +1,202 @@
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asv_bench/benchmarks/algos/isin.py

@@ -9,6 +9,8 @@
  date_range,
 )
 
+from ..pandas_vb_common import tm
+
 
 class IsIn:
 
@@ -22,6 +24,9 @@ class IsIn:
  "datetime64[ns]",
  "category[object]",
  "category[int]",
+ "str",
+ "string",
+ "arrow_string",
  ]
  param_names = ["dtype"]
 
@@ -57,6 +62,15 @@ def setup(self, dtype):
  self.values = np.random.choice(arr, sample_size)
  self.series = Series(arr).astype("category")
 
+ elif dtype in ["str", "string", "arrow_string"]:
+ from pandas.core.arrays.string_arrow import ArrowStringDtype # noqa: F401
+
+ try:
+ self.series = Series(tm.makeStringIndex(N), dtype=dtype)
+ except ImportError:
+ raise NotImplementedError
+ self.values = list(self.series[:2])
+
  else:
  self.series = Series(np.random.randint(1, 10, N)).astype(dtype)
  self.values = [1, 2]

asv_bench/benchmarks/frame_methods.py

@@ -563,6 +563,14 @@ def time_frame_nunique(self):
  self.df.nunique()
 
 
+class SeriesNuniqueWithNan:
+ def setup(self):
+ self.ser = Series(100000 * (100 * [np.nan] + list(range(100)))).astype(float)
+
+ def time_series_nunique_nan(self):
+ self.ser.nunique()
+
+
 class Duplicated:
  def setup(self):
  n = 1 << 20