testing.assert_array_equal(data['endog'], y_exp) 浏览完整代码 来源:test_data.py 项目:philippmuller/statsmodels 示例28 def test_remove(self): ts = tm.makeTimeSeries() df = tm.makeDataFrame() self.store['a'] = ts self.store['b'] = df self.store.remove('a') self.assertEquals(len...
Currently from narwhals.stable.v1.dependencies import is_pandas_like_dataframe raises, but from narwhals.stable.v1 import dependencies passes
from pandarallel import pandarallel pandarallel.initialize(nb_workers=min(os.cpu_count(), 12)) def parapply_only_used_cols(df: pd.DataFrame, remove_col: str, words_to_remove_col: str) -> list[str]: return df[[remove_col, words_to_remove_col]].parallel_apply( lambda x: remove_words...
(df.columns) # Split annotations file df_train = pd.DataFrame(columns=columnlist) df_test = pd.DataFrame(columns=columnlist) # Make test and train directories inside the outdir data_train_path = os.path.join(outdir, "train", "data") target_train_path = os.path.join(outdir, "train"...
from sklearn.model_selection import cross_validate classifier = RandomForestClassifier() scores = cross_validate( classifier, X, y, cv=10, scoring=['accuracy', 'precision', 'recall', 'f1','r2', 'neg_mean_squared_error'] ) scores = pd.DataFrame(scores) scores.mean() #output fit_tim...
4.make_blobs数据集中的x是二维数组,特征,可以通过重采样reshape(-1,n)/这里的n是指数组特征多少来判断,可以将dataframe转化为array,y是一维数组,是特征值,自己喂的数据也要通过 df['sign'].values的方式,将series转化为array格式才可以放入到这些机器学习模型当中。
tm.makeMixedDataFrame()]: result = isna_f(df) expected = df.apply(isna_f) tm.assert_frame_equal(result, expected)# panelwithcatch_warnings(record=True): simplefilter("ignore", FutureWarning)forpin[tm.makePanel(), tm.makePeriodPanel(), ...
在下文中一共展示了testing.makeCustomDataframe方法的15个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。 示例1: test_slice_locs_with_type_mismatch ▲点赞 6▼
A pandas DataFrame is returned.Only the training data is selected data = load_data()[0] selected_columns = ["baselineDAS", "Age", "Gender"] y = np.array(data["Response.deltaDAS"]) x = np.array(data[selected_columns]) #Build a method with the dictionary and another one with the ...
Both .to_numpy() and .values work similarly, and they both return a NumPy array with the data from the pandas DataFrame: The pandas documentation suggests using .to_numpy() because of the flexibility offered by two optional parameters: dtype: Use this parameter to specify the data type of ...