DataFrame.to_latex([buf, columns, …]) Render an object to a tabular environment table. DataFrame.to_stata(fname[, convert_dates, …]) A class for writing Stata binary dta files from array-like objects DataFrame.to_msgpack([path_or_buf, encoding]) ...
DataFrame.to_msgpack([path_or_buf, encoding]) msgpack (serialize) object to input file path DataFrame.to_gbq(destination_table, project_id) Write a DataFrame to a Google BigQuery table. DataFrame.to_records([index, convert_datetime64]) Convert DataFrame to record array. DataFrame.to_sparse([...
to_msgpack Stata read_stata to_stata Python Pickle Format read_pickle to_pickle Google Big Query read_gbq to_gbq Excel的 student.xlsx内容 data = pandas.read_excel() data类型为 DataFrame,修改data # 通过位置修改第0行的名字 data.iloc[0, 1] = 'tomcat' # 通过位置修改第1...
binaryFeatherread_featherto_feather binaryMsgpackread_msgpackto_msgpack binaryStataread_statato_stata binarySASread_sas binaryPython Pickleread_pickleto_pickle SQLSQLread_sqlto_sql SQLGoogleBig Queryread_gbqto_gbq 主要内容 文件读取 1.read_csv ...
binaryFeatherread_featherto_feather binaryMsgpackread_msgpackto_msgpack binaryStataread_statato_stata binarySASread_sas binaryPython Pickleread_pickleto_pickle SQLSQLread_sqlto_sql SQLGoogleBig Queryread_gbqto_gbq 主要内容 文件读取 1.read_csv ...
Pandas是Python语言中非常好用的一种数据结构包,包含了许多有用的数据操作方法。而且很多算法相关的库函数的输入数据结构都要求是pandas数据,或者有该数据的接口。 仔细看pandas的API说明文档,就会发现有好多有用的函数,比如非常常用的文件的读写函数就包括如下函数: ...
to_msgpack([path_or_buf, encoding]) msgpack (serialize) object to input file path to_period([freq, copy]) Convert Series from DatetimeIndex to PeriodIndex with desired to_pickle(path) Pickle (serialize) object to input file path. to_sparse([kind, fill_value]) Convert Series to SparseSeries...
to_long(*args, **kwargs) to_msgpack([path_or_buf, encoding]) msgpack (serialize) object to input file path to_pickle(path) Pickle (serialize) object to input file path. to_sparse([fill_value, kind]) Convert to SparsePanel to_sql(name, con[, flavor, schema, ...]) Write records...
read_msgpack 从指定文件中加载msgpack Pandas对象 read_orc 从ORC文件中读取数据,并将其转换为 Pandas DataFrame read_parquet 从Parquet文件中读取数据,并将其转换为 Pandas DataFrame read_pickle 从指定文件中加载pickled Pandas或其他pickled对象 read_sas 读取XPORT或SAS7BDAT格式的SAS(统计分析软件)文件 read_sql...
read_msgpack (experimental) to_msgpack (experimental) read_html to_html read_gbq (experimental) to_gbq (experimental) read_stata to_stata read_sas read_clipboard to_clipboard read_pickle to_pickle//速度比csv快 读取CSV文件: pd.read_csv('foo.csv') //读取CSV ...