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feat: update spark version for ydata-profiling (#1730)
* chore: update test pipeline to run higher spark version * chore: update spark test CI/CD pipeline. * chore: fix spark CI/CD * chore: remove make spark-ci * chore: add pytest to the dependencies * fix: fixing numba version due to visions * feat: update pyspark install * fix: pyproject * chore: fix makefile to run the tests * chore: tests for pyspark versions bigger than 3.4 * fix: add other pyspark versions to the tests * chore: use ubuntu-22.04 * chore: update test pipeline to run higher spark version * chore: update spark test CI/CD pipeline. * chore: fix spark CI/CD * chore: remove make spark-ci * chore: add pytest to the dependencies * fix: fixing numba version due to visions * feat: update pyspark install * fix: pyproject * chore: fix makefile to run the tests * chore: tests for pyspark versions bigger than 3.4 * fix: add other pyspark versions to the tests * chore: use ubuntu-22.04 * chore: remove unused timestamp
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‎.github/workflows/pull-request.yml‎

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jobs:
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commitlint:
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name: Lint commit message
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runs-on: ubuntu-24.04
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runs-on: ubuntu-22.04
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steps:
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- uses: actions/checkout@v4
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lint:
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if: github.actor != 'renovate[bot]'
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name: Lint source code
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runs-on: ubuntu-24.04
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runs-on: ubuntu-22.04
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steps:
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- uses: actions/checkout@v4
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validate-docs:
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name: Validate Docs
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runs-on: ubuntu-24.04
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runs-on: ubuntu-22.04
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steps:
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- uses: actions/checkout@v4

‎.github/workflows/tests.yml‎

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- run: codecov -F py${{ matrix.python-version }}-${{ matrix.os }}-${{ matrix.pandas }}-${{ matrix.numpy }}
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test_spark:
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runs-on: ${{ matrix.os }}
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continue-on-error: True
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runs-on: ubuntu-22.04
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continue-on-error: false
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strategy:
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matrix:
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os: [ ubuntu-22.04 ]
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python-version: [3.8]
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pandas: ["pandas>1.1"]
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spark: ["3.0.1"]
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hadoop: [ 2.7 ]
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numpy: ["numpy"]
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java_home: [ /usr/lib/jvm/java-8-openjdk-amd64 ]
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name: Tests Spark | python ${{ matrix.python-version }}, ${{ matrix.os }}, spark${{ matrix.spark }}, ${{ matrix.pandas }}, ${{ matrix.numpy }}
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env:
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JAVA_HOME: ${{ matrix.java_home }}
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SPARK_VERSION: ${{ matrix.spark }}
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HADOOP_VERSION: ${{ matrix.hadoop }}
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SPARK_DIRECTORY: ${{ github.workspace }}/../
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SPARK_HOME: ${{ github.workspace }}/../spark/
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YDATA_PROFILING_NO_ANALYTICS: ${{ matrix.analytics }}
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python-version: [ "3.9", "3.10", "3.11", "3.12" ]
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pyspark-version: [ "3.4" , "3.5" ]
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name: Tests Spark | Python ${{ matrix.python-version }} | PySpark ${{ matrix.pyspark-version }}
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steps:
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- uses: actions/checkout@v4
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- name: Setup python
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- name: Checkout Code
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uses: actions/checkout@v4
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- name: Install Java (OpenJDK 11)
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run: |
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sudo apt-get update
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sudo apt-get install -y openjdk-11-jdk
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echo "JAVA_HOME=/usr/lib/jvm/java-11-openjdk-amd64" >> $GITHUB_ENV
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echo "PATH=$JAVA_HOME/bin:$PATH" >> $GITHUB_ENV
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java -version
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- name: Setup Python
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uses: actions/setup-python@v5
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with:
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python-version: ${{ matrix.python-version }}
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architecture: x64
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- uses: actions/cache@v4
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if: startsWith(runner.os, 'Linux')
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- name: Cache pip dependencies
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uses: actions/cache@v4
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with:
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path: ~/.cache/pip
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key: ${{ runner.os }}-${{ matrix.pandas }}-pip-${{ hashFiles('**/requirements.txt') }}
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key: pip-${{ runner.os }}-${{ matrix.python-version }}-${{ matrix.pyspark-version }}-${{ hashFiles('requirements/*.txt', 'setup.cfg', 'pyproject.toml') }}
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restore-keys: |
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${{ runner.os }}-${{ matrix.pandas }}-pip-\
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- uses: actions/cache@v4
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if: startsWith(runner.os, 'macOS')
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with:
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path: ~/Library/Caches/pip
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key: ${{ runner.os }}-${{ matrix.pandas }}-pip-${{ hashFiles('**/requirements.txt') }}
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restore-keys: |
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${{ runner.os }}-${{ matrix.pandas }}-pip-
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- uses: actions/cache@v4
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if: startsWith(runner.os, 'Windows')
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with:
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path: ~\AppData\Local\pip\Cache
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key: ${{ runner.os }}-${{ matrix.pandas }}-pip-${{ hashFiles('**/requirements.txt') }}
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restore-keys: |
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${{ runner.os }}-${{ matrix.pandas }}-pip-
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- run: |
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pip install --upgrade pip setuptools wheel
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pip install pytest-spark>=0.6.0 pyarrow==1.0.1 pyspark=="${{ matrix.spark }}"
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pip-${{ runner.os }}-
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- name: Install Dependencies
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run: |
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python -m pip install --upgrade pip setuptools wheel
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pip install pyarrow>4.0.0 pyspark=="${{ matrix.pyspark-version }}" --no-cache-dir
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echo "ARROW_PRE_0_15_IPC_FORMAT=1" >> $GITHUB_ENV
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echo "SPARK_LOCAL_IP=127.0.0.1" >> $GITHUB_ENV
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- name: Run Tests
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run: |
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make install
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pip install ".[test]"
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pip install "${{ matrix.pandas }}" "${{ matrix.numpy }}"
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- if: ${{ matrix.spark != '3.0.1' }}
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run: echo "ARROW_PRE_0_15_IPC_FORMAT=1" >> $GITHUB_ENV
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- run: echo "SPARK_LOCAL_IP=127.0.0.1" >> $GITHUB_ENV
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- run: make install
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- run: make install-spark-ci
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- run: pip install ".[spark]" # Make sure the proper version of pandas is install after everything
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- run: make test_spark
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make test_spark
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‎Makefile‎

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ydata_profiling -h
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test_spark:
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pytest --spark_home=${SPARK_HOME} tests/backends/spark_backend/
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pytest tests/backends/spark_backend/
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ydata_profiling -h
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test_cov:
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install-spark-ci:
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sudo apt-get update
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sudo apt-get -y install openjdk-8-jdk
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sudo apt-get -y install openjdk-11-jdk
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curl https://archive.apache.org/dist/spark/spark-${SPARK_VERSION}/spark-${SPARK_VERSION}-bin-hadoop${HADOOP_VERSION}.tgz \
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--output ${SPARK_DIRECTORY}/spark.tgz
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cd ${SPARK_DIRECTORY} && tar -xvzf spark.tgz && mv spark-${SPARK_VERSION}-bin-hadoop${HADOOP_VERSION} spark

‎pyproject.toml‎

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"imagehash==4.3.1",
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"wordcloud>=1.9.3",
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"dacite>=1.8",
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"numba>=0.56.0, <1",
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"numba>=0.56.0, <=0.61",
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]
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dynamic = [
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# note that if you are using pyspark 2.3 or 2.4 and pyarrow >= 0.15, you might need to
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# set ARROW_PRE_0_15_IPC_FORMAT=1 in your conf/spark-env.sh for toPandas functions to work properly
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spark = [
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"pyspark>=2.3.0",
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"pyarrow>=2.0.0",
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"pandas>1.1, <2, !=1.4.0",
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"numpy>=1.16.0,<1.24",
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"pyspark>=3.0",
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"pyarrow>=4.0.0",
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"pandas>1.1",
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"numpy>=1.16.0",
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"visions[type_image_path]>=0.7.5, <0.7.7",
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]
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‎tests/backends/spark_backend/test_descriptions_spark.py‎

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"s1": np.ones(9),
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"s2": ["some constant text $ % value {obj} " for _ in range(1, 10)],
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"somedate": [
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datetime.datetime(2011, 7, 4),
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datetime.datetime(2022, 1, 1, 13, 57),
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datetime.datetime(1990, 12, 9),
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datetime.date(2011, 7, 4),
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datetime.date(2011, 7, 2),
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datetime.date(1990, 12, 9),
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pd.NaT,
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datetime.datetime(1990, 12, 9),
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datetime.datetime(1970, 12, 9),
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datetime.datetime(1972, 1, 2),
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datetime.datetime(1970, 12, 9),
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datetime.datetime(1970, 12, 9),
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datetime.date(1990, 12, 9),
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datetime.date(1970, 12, 9),
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datetime.date(1972, 1, 2),
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datetime.date(1970, 12, 9),
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datetime.date(1970, 12, 9),
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],
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"bool_tf": [True, True, False, True, False, True, True, False, True],
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"bool_tf_with_nan": [
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if column == "mixed":
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describe_data[column] = [str(i) for i in describe_data[column]]
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if column == "bool_tf_with_nan":
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elif column == "bool_tf_with_nan":
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describe_data[column] = [
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True if i else False for i in describe_data[column] # noqa: SIM210
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]
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pdf = pd.DataFrame({column: describe_data[column]}) # Convert to Pandas DataFrame
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# Ensure NaNs are replaced with None (Spark does not support NaN in non-float columns)
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pdf = pdf.where(pd.notna(pdf), None)
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sdf = spark_session.createDataFrame(pdf)
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results = describe(cfg, sdf, summarizer_spark, typeset)

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