df (df (column_name”).isin ([value1, ' value2 '])) # Using isin for filtering rows df[df['Customer Country'].isin(['United States', 'Puerto Rico'])] # Filter rows based on values in a list and select spesific columns df[["Customer Id", "Order Region"]][df['Order Region'...
df (df (column_name”).isin ([value1, ' value2 '])) # Using isin for filtering rows df[df['Customer Country'].isin(['United States', 'Puerto Rico'])] # Filter rows based on values in a list and select spesific columns df[["Customer Id", "Order Region"]][df['Order Region'...
df (df (column_name”).isin ([value1, ' value2 '])) 复制 # Using isinforfiltering rows df[df['Customer Country'].isin(['United States','Puerto Rico'])] 1. 2. 复制 # Filter rows based on valuesina list and select spesific columns df[["Customer Id","Order Region"]][df['Orde...
df[df['column_name'].between(start, end)] 代码语言:javascript 代码运行次数:0 运行 AI代码解释 # Filter rows based on values within a range df[df['Order Quantity'].between(3,5)] 字符串方法:根据字符串匹配条件筛选行。例如str.startswith(), str.endswith(), str.contains() 代码语言:javascri...
isin([]):基于列表过滤数据。df (df (column_name”).isin ([value1, ' value2 '])) #Usingisinforfilteringrowsdf[df['Customer Country'].isin(['United States','Puerto Rico'])] #Filterrowsbasedonvaluesina listandselectspesificcolumnsdf[["Customer Id", "Order Region"]][df['Order Region'...
('value1').alias('mean_value1'), pl.sum('value2').alias('sum_value2') ]) group_time_pl = time.time() - start # 打印结果 print(f"Polars CPU加载时间: {load_time_pl:.4f} 秒") print(f"Polars CPU 过滤时间: {filter_time_pl:.4f} 秒") print(f"Polars CPU 分组聚合时间: {...
Filter by Column Value:To select rows based on a specific column value, use the index chain method. For example, to filter rows where sales are over 300: Pythongreater_than = df[df['Sales'] > 300] This will return rows with sales greater than 300.Filter by Multiple Conditions:...
DataFrame.insert(loc, column, value[, …])在特殊地点插入行 DataFrame.iter()Iterate over infor axis DataFrame.iteritems()返回列名和序列的迭代器 DataFrame.iterrows()返回索引和序列的迭代器 DataFrame.itertuples([index, name])Iterate over DataFrame rows as namedtuples, with index value as first elem...
DataFrame.filter([items, like, regex, axis]) 过滤特定的子数据框 DataFrame.first(offset) Convenience method for subsetting initial periods of time series data based on a date offset. DataFrame.head([n]) 返回前n行 DataFrame.idxmax([axis, skipna]) ...
我們可以根據單列或多列值選擇DataFrame的行。我們也可以從 DataFrame 中獲得滿足或不滿足一個或多個條件的行。這可以通過布林索引,位置索引,標籤索引和 query()方法來實現。 根據特定的列值選擇 Pandas 行 我們可以從包含或不包含列的特定值的 DataFrame 中選擇 Pandas 行。它廣泛用於根據列值過...