df.select_dtypes(include = 'number').head() 1. 2. df.loc[:,(df.dtypes=='int64') | (df.dtypes=='float64')].head() 1.
7、按数据类型查询 df.select_dtypes(include=['float64']) # 选择float64型数据 df.select_dtypes(include='bool') df.select_dtypes(include=['number']) # 只取数字型 df.select_dtypes(exclude=['int']) # 排除int类型 df.select_dtypes(exclude=['datetime64']) 02、数据类型转换 在开始数据分析前...
selector = SequentialFeatureSelector(estimator=model, n_features_to_select=10, direction='backward', cv=2) selector.fit_transform(X,y) # check names of features selected feature_names = np.array(X.columns) feature_names[selector.get_support] >> array(['bore','make_mitsubishi','make_niss...
可以使用df.select_dtypes(include=[np.number])来选择数值型列。 python import numpy as np # 计算每列的平均值(只考虑数值型列) numeric_cols = df.select_dtypes(include=[np.number]).columns column_means = df[numeric_cols].mean() 3. 定义一个函数,判断行中多列的值是否同时大于各自列的平均值...
# 筛选出数值型列 numeric_df = df.select_dtypes(include=['number']) # 计算每一列的总和 sums_list = numeric_df.sum().tolist() print(sums_list) # 输出: [6, 15, 24] 问题2: DataFrame中存在缺失值(NaN) 如果DataFrame中存在缺失值,sum()方法默认会忽略这些缺失值,但有时你可能需要特别处理这...
df['total'] =df.select_dtypes(include=['int']).sum(1)df['total'] = df.loc[:,'Q1':'Q4'].apply(lambda x: sum(x), axis='columns') df.loc[:,'Q10'] ='我是新来的'# 也可以 # 增加一列并赋值,不满足条件的为NaN df.loc[df.num >= 60,'成绩'] ='合格' ...
DataFrame.select_dtypes([include, exclude])根据数据类型选取子数据框 DataFrame.valuesNumpy的展示方式 DataFrame.axes返回横纵坐标的标签名 DataFrame.ndim返回数据框的纬度 DataFrame.size返回数据框元素的个数 DataFrame.shape返回数据框的形状 DataFrame.memory_usage([index, deep])Memory usage of DataFrame columns...
``numpy.number``. To exclude object columns submit the data type ``numpy.object``. Strings can also be used in the style of ``select_dtypes`` (e.g. ``df.describe(include=['O'])``). To exclude pandas categorical columns, use ``'category'`` ...
select_dtypes(include=['datetime']).columns: df[col] = df[col].astype(str) df.fillna("", inplace=True) data_li = df.to_dict(orient='records') res_data = { 2 changes: 2 additions & 0 deletions 2 web_apps/llm/agents/data_chat_agent.py Original file line numberDiff line number...
We read every piece of feedback, and take your input very seriously. Include my email address so I can be contacted Cancel Submit feedback Saved searches Use saved searches to filter your results more quickly Cancel Create saved search Sign in Sign up Reseting focus {...