import polars as pl import time # 读取 CSV 文件 start = time.time() df_pl_gpu = pl.read_csv('test_data.csv') load_time_pl_gpu = time.time() - start # 过滤操作 start = time.time() filtered_pl_gpu = df_pl_gpu.filter(pl
In [516]: store.select("dfq", where="A>0 or C>0") Out[516]: A B C D 2013-01-02 0.658179 0.362814 -0.917897 0.010165 2013-01-03 0.905122 1.848731 -1.184241 0.932053 2013-01-05 -0.830545 -0.457071 1.565581 1.148032 2013-01-06 0.431186 1.049421 0.383309 0.595013 2013-01-07 0.617509 -...
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]) #Return index of first occurrence of maximum over...
从Excel文件中读取数据pandas.read_excel(io,sheet_name,index_col=None,header=0,usecols=None,nrows=None,na_values=None,na_filter=True) io:文件名。 sheet_name:表格名 index_col:指定作为行索引的列。 header:指定作为列名的行。默认为0,表示把第一行作为列名。 usecols:指定要读取的列。 nrows:要读取...
To filter grades greater than 90 OR with a status of ‘Fail’: high_or_fail = df.where((df['Grade'] > 90) | (df['Status'] == 'Fail')) print(high_or_fail) Output: Grade Status 0 NaN NaN 1 NaN NaN 2 78.0 Fail 3 NaN NaN ...
=file("orders_filter.txt").export@tc(A2) 得益于游标机制,SPL 不必手工区分首次创建文件和后续追加,代码简短得多。 排序 pandas: def parse_type(s): if s.isdigit(): return int(s) try: res = float(s) return res except: return s def pos_by(by,head,sep): by_num = 0 for col in head...
Return a DataFrame with only the "name" and "age" columns:import pandas as pddata = { "name": ["Sally", "Mary", "John"], "age": [50, 40, 30], "qualified": [True, False, False]}df = pd.DataFrame(data)newdf = df.filter(items=["name", "age"]) ...
filter() Filter the DataFrame according to the specified filter first() Returns the first rows of a specified date selection floordiv() Divides the values of a DataFrame with the specified value(s), and floor the values ge() Returns True for values greater than, or equal to the specified ...
na_filter=True,verbose=False,skip_blank_lines=True,parse_dates=False,infer_datetime_format=False,keep_date_col=False,date_parser=None,dayfirst=False,iterator=False,chunksize=None,compression='infer',thousands=None,decimal=b'.',lineterminator=None,quotechar='"',quoting=0,escapechar=None,comment=...
groups.filter()过滤数据 一些方法详解: Groupby对象 GroupBy对象是pandas.DataFrame.groupby(), pandas.Series.groupby()调用的返回值。 GroupBy.count():计算每列的统计数,不包括NaN. SeriesGroupby.nlargest(3) 返回分组后的Series的前3个最大值。 df = pd.DataFrame({'grps': list('aaabbcaabcccbbc'),'val...