import pandas #导入pandas模块 from pandas import read_excel #导入read_execel file='d:/student.xlsx' #变量file表示文件路径,注意'/'的用法 数据见第18章表18-1 df=read_excel(file,sheet_name=0,converters={'学号':str}) #将Excel文件导入到DataFrame变量中 df=df[:5] #截取df的前5个记录 print(...
print(pd.DataFrame(rows, columns=[x[0] for x in cursor.description])) print(’---’)import sqlalchemy as sqla db = sqla.create_engine(‘sqlite:///mydata.sqlite’) print(pd.read_sql(‘select * from test’, db)) 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12....
compile("^九.{1}备注说明") # 抽取模式,不校验数据的准确性 def docx_read(file1): # 定义接受当前文档的part_4和part_8 part_all_dict_new = {} # print("当前文件:===>",os.path.join("",file1)) document = Document(os.path.join("",file1)) # df=pd.DataFrame(columns =['总学分'...
help(pd.read_csv) 1. 一、文本文件 1、纯文本文件 AI检测代码解析 filename = 'demo.txt' file = open(filename, mode='r') # 打开文件进行读取 text = file.read() # 读取文件的内容 print(file.closed) # 检查文件是否关闭 file.close() # 关闭文件 ...
Quit() def docx_read(file1): # 定义接受当前文档的part_4和part_8 part_all_dict_new = {} # print("当前文件:===>",os.path.join("",file1)) document = Document(os.path.join("",file1)) # df=pd.DataFrame(columns =['总学分','课内学分','课内学分占比','实践教学学分','实践教...
int) from sklearn.tree import DecisionTreeClassifier as DTC dtc = DTC(criterion='entropy') dtc.fit(x, y) from sklearn.tree import export_graphviz from sklearn.externals.six import StringIO with open("tree.dot", 'w') as f: f = export_graphviz(dtc, feature_names=x.columns, out_file...
columns=[row['account_key']forrowinreader] #直接根据想要提取的列名称读取,不能根据列号读取 print(columns) #返回list类型 out:['448', '448', '448', '448', '448', '448', '448', '448', '448', '700', '429', '429', '60', '60'……] ...
FROM store_returns GROUP BY sr_customer_sk ) returned ON ss_customer_sk=sr_customer_sk'''# Define the columns we wish to import.column_info = {"customer": {"type":"integer"},"orderRatio": {"type":"integer"},"itemsRatio": {"type":"integer"},"frequency": {"type...
import polars as pl pl_data = pl.read_csv(data_file, has_header=False, new_columns=col_list) 运行apply函数,记录耗时: pl_data = pl_data.select([ pl.col(col).apply(lambda s: apply_md5(s)) for col in pl_data.columns ]) 查看运行结果: 3. Modin测试 Modin特点: 使用DataFrame作为基本...
df = pd.read_excel("test.xlsx", dtype=str, keep_default_na='') df.drop(columns=['寄件地区'], inplace=True) 5、列表头改名(补充) 如下:将某列表头【到件地区】修改为【对方地区】 df = pd.read_excel("test.xlsx", dtype=str, keep_default_na='') df = df.rename(columns={'到件地区...