接下来,我们可以使用filter函数根据条件筛选数据。例如,我们想要筛选出年龄大于等于18岁的数据,可以使用以下代码: 代码语言:txt 复制 filtered = grouped.filter(lambda x: x['年龄'] >= 18) 这将返回一个新的DataFrame,其中包含满足条件的数据。 综合起来,我们...
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'].isin(['Central America', 'Caribbean'])] # Using NOT isin for filtering rows df[~df['C...
def create_points_df(self): # Convert points list to xy coordinates. xy_lat_lon_list = [convert_to_xy(l_xy) for l_xy in self.lat_lon_list] # Midpoint between gdt1 and every point in xy. midpoints_xy = [get_midpoint(gdt1_xy, point) for point in xy_lat_lon_list] # Conve...
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Example 1: Filter Pandas DataFrame Based on the Index To select the row with the index of 2 (for the “Monitor’” product) while filtering out all the other rows: Copy df_filter = df.filter(items=[2], axis=0) So the completePythoncode is: ...
使用的 Dataframe ：
在Pandas中,可以使用OR运算符和.filter()方法来实现数据筛选。 使用OR运算符: OR运算符用于同时满足多个条件中的任意一个。在Pandas中,可以使用|符号表示OR运算符。 示例代码: 示例代码: 上述示例中,使用OR运算符筛选出年龄大于30岁或者薪水大于6500的行。
Bottom line:Please usequerywhen querying or filtering rows based on a conditional expression. --貌似作者建议尽量用query函数。 for filter in result_filter: # logging.debug('filter kpi name [%s]' % (filter['kpi'].name)) if filter['kpi'].name in result_df: ...
# Using a series of booleans to filter df[df.rain_octsep < 1000] 1. 2. 这条代码只返回十月-九月降雨量小于 1000 mm 的记录: 也可以通过复合条件表达式来进行过滤: # Filtering by multiple conditionals df[(df.rain_octsep < 1000) & (df.outflow_octsep < 4000)] # Can't use the keyword...
# max minus mix lambda fn fn = lambda x: x.max() - x.min() # Apply this on dframe that we've just created above dframe.apply(fn) isin() lsin () 用于过滤数据帧。Isin () 有助于选择特定列中具有特定(或多个)值的行。 # Using the dataframe we created for read_csv filter1 = ...