print(f"The mean of the data is {mean}") 示例2:计算中位数 python import statistics data = [1, 3, 5, 7, 9] median = statistics.median(data) print(f"The median of the data is {median}") 示例3:计算众数 请注意,statistics模块本身不提供直接计算众数的函数,但你可以使用collections.Counter...
# statisticsstatistics = LazyImport("import statistics") ### Machine Learningsklearn = LazyImport("import sklearn")OneHotEncoder = LazyImport("from sklearn.preprocessing import OneHotEncoder")TSNE = LazyImport("from sklearn.manifold import TSNE")train_test_split = LazyImport("from sklearn.model...
pydot=LazyImport("import pydot") #statistics statistics=LazyImport("import statistics") ###MachineLearning sklearn=LazyImport("import sklearn") OneHotEncoder=LazyImport("from sklearn.preprocessing import OneHotEncoder") TSNE=LazyImport("from sklearn.manifold import TSNE") train_test_split=LazyImpor...
expressaspx")dash = LazyImport("import dash")bokeh = LazyImport("import bokeh")alt = LazyImport("import altairasalt")pydot = LazyImport("import pydot")# statisticsstatistics = LazyImport("import statistics")### Machine Learningsklearn = LazyImport("import sklearn")OneHotEncoder = LazyImport...
as sns")py=LazyImport("import plotly as py")go=LazyImport("import plotly.graph_objs as go")px=LazyImport("import plotly.express as px")dash=LazyImport("import dash")bokeh=LazyImport("import bokeh")alt=LazyImport("import altair as alt")pydot=LazyImport("import pydot")# statistics ...
("import pydot") # statistics statistics = LazyImport("import statistics") ### Machine Learning sklearn = LazyImport("import sklearn") OneHotEncoder = LazyImport("from sklearn.preprocessing import OneHotEncoder") TSNE = LazyImport("from sklearn.manifold import TSNE") train_test_split = ...
上述代码中,我们使用Python内置的statistics模块来提供快速和简便的数学和统计功能。 2. 使用自定义模块 在创建了grades.py模块后,我们可以在另一个Python文件中导入并使用它。接下来,我们将使用一个名为main.py的文件来实现这一点。 # main.pyfromgradesimportcalculate_statisticsimportmatplotlib.pyplotasplt# 假设班级...
output_df = pd.DataFrame({'Values':[adft[0], adft[1], adft[4]['1%']], 'Metric':['Test Statistics', 'p-value', 'critical value (1%)']}) print('Statistics of {} sensor:\n'.format(sensor), output_df) print if (adft[1] < 0.05) & (adft[0] < adft[4]['1%']): ...
'_statistics','_string','_struct','_symtable','_thread','_tracemalloc','_warnings','_weakref','_winapi','_xxsubinterpreters','array','atexit','audioop','binascii','builtins','cmath','errno','faulthandler','gc','itertools','marshal','math','mmap','msvcrt','nt','parser','...
StatisticsError StatisticsWarning StatusAlert StatusAlertOutline StatusChangedInline StatusError StatusErrorNew StatusErrorNoColor StatusErrorOutline StatusExcluded StatusExcludedOutline Фильтрсостояния StatusHelp StatusHelpOutline StatusHidden StatusInformation StatusInformationNoColor StatusInformation...