Pandas Input/Output API Manual

Pandas is a powerful Python data analysis library that provides a large number of data manipulation tools, including data input and output (I/O).

The following are commonly used Pandas Input/Output APIs:

Reading Data

Method Description
pd.read_csv(filepath, sep, header, index_col) Read data from a CSV file.
pd.read_excel(io, sheet_name) Read data from an Excel file.
pd.read_json(path_or_buf) Read data from a JSON file.
pd.read_html(io) Read table data from an HTML file.
pd.read_sql(sql, con) Read data from a SQL database.
pd.read_clipboard() Read data from the clipboard.
pd.read_parquet(path) Read data from a Parquet file.
pd.read_feather(path) Read data from a Feather file.
pd.read_hdf(path, key) Read data from an HDF5 file.
pd.read_pickle(path) Read data from a Pickle file.
pd.read_sas(filepath) Read data from a SAS file.
pd.read_spss(filepath) Read data from an SPSS file.
pd.read_sql_table(table_name, con) Read data from a table in a SQL database.
pd.read_sql_query(sql, con) Execute a SQL query and read the results.
pd.read_gbq(query) Read data from Google BigQuery.

Writing Data

Method Description
DataFrame.to_csv(path, sep, index) Write a DataFrame to a CSV file.
DataFrame.to_excel(path, sheet_name) Write a DataFrame to an Excel file.
DataFrame.to_json(path) Write a DataFrame to a JSON file.
DataFrame.to_html(path) Write a DataFrame to an HTML file.
DataFrame.to_sql(name, con) Write a DataFrame to a SQL database.
DataFrame.to_clipboard() Copy a DataFrame to the clipboard.
DataFrame.to_parquet(path) Write a DataFrame to a Parquet file.
DataFrame.to_feather(path) Write a DataFrame to a Feather file.
DataFrame.to_hdf(path, key) Write a DataFrame to an HDF5 file.
DataFrame.to_pickle(path) Write a DataFrame to a Pickle file.
DataFrame.to_markdown(path) Write a DataFrame to a Markdown file.
DataFrame.to_string() Convert a DataFrame to a string.
DataFrame.to_latex(path) Write a DataFrame to a LaTeX file.
DataFrame.to_records() Convert a DataFrame to a numpy record array.
DataFrame.to_dict() Convert a DataFrame to a dictionary.
DataFrame.to_numpy() Convert a DataFrame to a numpy array.

Examples

Examples

import pandas as pd

# Read CSV file
df = pd.read_csv('data.csv')

# Read Excel file
df_excel = pd.read_excel('data.xlsx', sheet_name='Sheet1')

# Read JSON file
df_json = pd.read_json('data.json')

# Write CSV file
df.to_csv('output.csv', index=False)

# Write Excel file
df.to_excel('output.xlsx', sheet_name='Sheet1')

# Write JSON file
df.to_json('output.json')

Detailed Parameter Description

pd.read_csv()

Parameter Description
filepath File path.
sep Delimiter, default is,。
header Specify the row number used as column names, default is0(First row).
index_col Specify the column number or column name used as the index.
dtype Specify the data type of the columns.
na_values Specify which values should be treated as missing values.

DataFrame.to_csv()

Parameter Description
path File path.
sep Delimiter, default is,。
index Whether to write the index, default isTrue。
header Whether to write column names, default isTrue。
encoding File encoding, default isutf-8。

pd.read_excel()

Parameter Description
io File path or file object.
sheet_name Worksheet name or index, default is0。
header Specify the row number used as column names, default is0。
index_col Specify the column number or column name used as the index.

DataFrame.to_excel()

Parameter Description
path File path.
sheet_name Worksheet name, default isSheet1。
index Whether to write the index, default isTrue。
header Whether to write column names, default isTrue。

For more detailed information, please refer toPandas Official Documentation。

Other Extensions