pip install pytest 然后,在Python脚本或交互式环境中导入assert_frame_equal()函数: from pandas.util.testing import assert_frame_equal 接下来,使用assert_frame_equal()函数来比较两个DataFrame: assert_frame_equal(df1, df2) # 如果df1和df2相
pandas.testing.assert_frame_equal(left, right, check_dtype=True, check_index_type='equiv', check_column_type='equiv', check_frame_type=True, check_less_precise=NoDefault.no_default, check_names=True, by_blocks=False, check_exact=False, check_datetimelike_compat=False, check_categorical=True,...
Pandas的testing模块中有一个assert_frame_equal()方法,可以用来比较两个数据框是否完全相同。assert_frame_equal()方法比较两个数据框的每个元素,并在两个数据框不相同时抛出一个AssertionError异常。示例代码如下: importpandasaspdfrompandas.testingimportassert_frame_equal# 定义数据框1df1=pd.DataFrame({'A':[1...
assert_frame_equal是比较两个df是否完全一模一样。index都要一样! import pandas as pd import numpy as np from pandas.testing import assert_frame_equal df1 = pd.DataFrame(np.arange(12).reshape(3, -1)) df2 = pd.DataFrame(np.arange(12).reshape(3, -1)) df1 == df2 assert_frame_equal(df1...
print(pd.testing.assert_series_equal(df.a, df.b, check_names=False, check_dtype=False)) print() # assert_frame_equal函数查看是否相同,异常则输出 df_new = df.copy() pd.testing.assert_frame_equal(df, df_new) # Use NumPy without importing NumPy ...
Method/Function:assert_frame_equal 导入包:pandasutiltesting 每个示例代码都附有代码来源和完整的源代码,希望对您的程序开发有帮助。 示例1 deftest_groupby_to_series_to_frame_2(self):df=pd.DataFrame({'a':[6,2,2],'b':[4,5,6]})labels=['g1','g1','g2']benchmark=df.groupby(labels).ap...
It'd be a fantastic time saver to have a function or some sort of testing suite which is ready to use within PyArrow itself! Perhaps something like apa.testing.assert_table_equals()which could help with repetitive tasks like this without the cost of conversion into another package's format ...
testing.assert_frame_equal(left, right[, …]):检查左右DataFrame是否相等。 testing.assert_series_equal(left, right[, …]):检查左右系列是否相等。 testing.assert_index_equal(left, right[, …]):检查左右索引是否相等。 例外and 警告 errors.DtypeWarning :从文件中读取列中的不同dtypes时出现警告。 err...
Pandas有一个assert_frame_equal方法,也可以判断DataFrame是否相同: 代码语言:javascript 代码运行次数:0 运行 AI代码解释 >>> from pandas.testing import assert_frame_equal >>> assert_frame_equal( ... movie_boolean, movie_mask, check_dtype=False ... ) 更多 比较这两个条件的速度: 代码语言:javascript...
assert_frame_equal()来自pandas.testing包，而不是unittest.TestCase类。替换：如果你导入这个，问题就...