// eg. getcwd, see: https://man7.org/linux/man-pages/man3/getcwd.3.html // so we need to check if the buffer is allocated by jemalloc // if not, we need to free it by glibc free arena_ind = je_mallctl("arenas.l
In [32]: %%time ...: files = pathlib.Path("data/timeseries/").glob("ts*.parquet") ...: counts = pd.Series(dtype=int) ...: for path in files: ...: df = pd.read_parquet(path) ...: counts = counts.add(df["name"].value_counts(), fill_value=0) ...: counts.astype(in...
print('Check file size on disk:')!du-h chicago_taxi_2013_2020.csvprint()df=vaex.open('chicago_taxi_2013_2020.csv')print(f'Number of rows:{df.shape[0]:,}')print(f'Number of columns:{df.shape[1]}')mean_tip_amount=df.tip_amount.mean(progress='widget')print(f'Mean tip amount:{...
# Random integersarray = np.random.randint(20, size=12)arrayarray([ 0, 1, 8, 19, 16, 18, 10, 11, 2, 13, 14, 3])# Divide by 2 and check if remainder is 1cond = np.mod(array, 2)==1condarray([False, True, False, True, False, ...
查看数据框的行数:len(df); 查看数据框的行数和列数 - shape:df.shape(); 查看数据框的大小:df.size; 查看数据框的概要信息:df.info(),返回的是 shape,各列的非缺失值个数、数据类型; 查看各变量的数据类型:df.dtypes; 查看df的表格内容:df.values; 查看df的各个列名称:df.columns; 重命名列:df...
# Check memory usage after conversion print("Memory usage after conversion:") print(df_large.memory_usage().sum()) 输出 Memory usage before conversion: 16000128 Memory usage after conversion: 5000128 2. 加载较少的数据 概述:这种技术只需要从数据集中加载相关列。这在处理具有大量列的数据集或分析仅...
df= pd.DataFrame({'date_col': date_col,'str_col': str_col,'float_col': float_col,'int_col': int_col}) df.info() df.head() 以不同的格式存储 接下来创建测试函数,以不同的格式进行读写。 importtimeimport os defcheck_read_write_size(df, file_name, compression= None) : ...
[27], line 1 ---> 1 df.apply(f, axis="columns") File ~/work/pandas/pandas/pandas/core/frame.py:10374, in DataFrame.apply(self, func, axis, raw, result_type, args, by_row, engine, engine_kwargs, **kwargs) 10360 from pandas.core.apply import frame_apply 10362 op = frame_apply...
df: DataFrame类型,生成的DataFrame 2.3.1.1 dtypes属性 属性调用: fmt = df.dtypes 属性功能:返回数据结构中每列的数据类型(由于是多个,使用dtypes,numpy中单个,使用dtype) 属性参数: fmt fmt: Series类型,包含每个数据值的数据类型,index为列名,value为类型,其中,object类型相当于Python中的string ...
pandas python中的函数，用于从交易池中删除未购买特定品牌/商品的用户这个应该够了。1.步骤1创建一个...