Creating, Reading and Writing

Table of contents

1. Creating
   1. pandas DataFrame
   2. pandas Series
2. Reading
3. Writing

import pandas as pd

Creating

pandas DataFrame

pd.DataFrame(data, index, columns, dtype)

pandas document - pandas.DataFrame

1. data : ndarray (structured or homogeneous), Iterable, dict, or DataFrame
   • List-like of List-like : 각 List 는 row 를 나타냄
   • List-like of Dict : 각 Dict 는 row 를 나타냄
     • Dict 의 key : columns 의 이름
       Dict 의 values : columns 의 성분
   • Dict of List-like : 각 List 는 column 을 나타냄
2. index : Index or array-like
3. columns : Index or array-like
4. dtype : dtype, default None

pandas Series

pandas.Series 는 기본적으로 DataFrame 의 하나의 row data

pd.Series(data, index, name, dtype)

pandas document - pandas.Series

1. data : array-like, Iterable, dict, or scalar value
2. index : array-like or Index (1d)
3. name : str, optional
4. dtype : str, numpy.dtype, or ExtensionDtype, optional

Reading

pd.read_csv(filepath_or_buffer, index_col, header, names)

pandas document - pandas.read_csv

1. filepath_or_buffer : str, path object or file-like object
2. index_col : int, str, sequence of int / str, or False, optional, default None
   • which columns to row label?
3. header : int, list of int, None, default ‘infer’
   • which rows to column names?
4. names : array-like, optional
   • explicitly pass column names

Writing

pd.DataFrame.to_csv(path_or_buf, encoding)

pandas document - pandas.DataFrame.to_csv

1. path_or_buf : str, path object, file-like object, or None, default None
2. encoding : str, optional

pd.DataFrame.to_excel(excel_writer, encoding)

pandas document - pandas.DataFrame.to_excel

1. excel_writer : path-like, file-like, or ExcelWriter object
2. encoding : str, optional