import polars as pl import time # 读取 CSV 文件 start = time.time() df_pl = pl.read_csv('test_data.csv') load_time_pl = time.time() - start # 过滤操作 start = time.time() filtered_pl = df_pl.filter(pl.col('value1') > 50) filter_time_pl = time.time() - start # 分组...
Pandas Get Unique Values in Column Unique is also referred to as distinct, you can get unique values in the column using pandasSeries.unique()function, since this function needs to call on the Series object, usedf['column_name']to get the unique values as a Series. Syntax: # Syntax of ...
(self, key, value) 1284 ) 1285 1286 check_dict_or_set_indexers(key) 1287 key = com.apply_if_callable(key, self) -> 1288 cacher_needs_updating = self._check_is_chained_assignment_possible() 1289 1290 if key is Ellipsis: 1291 key = slice(None) ~/work/pandas/pandas/pandas/core/seri...
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...
value_counts().sort_values().tail(20).plot.line(title="Movies released in the last 20 years") 当然,有一些方法可以使这些图表更漂亮,甚至可以交互。 但是,使用Pandas,通过简单几行代码,不需要第三方工具包,就可以实现对数据更加直观的显示。 4. 数据ETL 目前数据ETL主要都是使用SQL,容易实现、可解释性...
Series 结构,也称 Series 序列,是 Pandas 常用的数据结构之一,它是一种类似于一维数组的结构,由一组数据值(value)和一组标签组成,其中标签与数据值之间是一一对应的关系。 Series 可以保存任何数据类型,比如整数、字符串、浮点数、Python 对象等,它的标签默认为整数,从 0 开始依次递增。Series 的结构图,如下所示...
In [8]: pd.Series(d) Out[8]: b1a0c2dtype: int64 如果传递了索引,则将从数据中与索引中的标签对应的值提取出来。 In [9]: d = {"a":0.0,"b":1.0,"c":2.0} In [10]: pd.Series(d) Out[10]: a0.0b1.0c2.0dtype: float64
In [432]: df.columns = pd.MultiIndex.from_product([["a"], ["b", "d"]], names=["c1", "c2"])In [433]: df.to_excel("path_to_file.xlsx")In [434]: df = pd.read_excel("path_to_file.xlsx", index_col=[0, 1], header=[0, 1])In [435]: dfOut[435]:c1 ac2 b dlv...
missing values in the dataset with a specific valuedf = df.fillna(0)# Replace missing values in the dataset with mediandf = df.fillna(df.median())# Replace missing values in Order Quantity column with the mean of Order Quantitiesdf['Order Quantity'].fillna(df["Order Quantity"].mean, in...
last) File ~/work/pandas/pandas/pandas/core/indexes/base.py:3805, in Index.get_loc(self, key) 3804 try: -> 3805 return self._engine.get_loc(casted_key) 3806 except KeyError as err: File index.pyx:167, in pandas._libs.index.IndexEngine.get_loc() File index.pyx:196, in pandas._...