How to read and save multi-format data files with Pandas

This article will explain in detail how to read and save multi-format data files in Pandas. The editor thinks it is very practical, so I share it for you as a reference. I hope you can get something after reading this article.

Code snippet:

# Pandas file reads and saves data to multiple format files # In [23]: import pandas as pd# In [24]: df = pd.read_csv ('data_price.csv') df.head () # set the index column to be saved as a new csv format file # In [25]: df.set_index (' Date') Inplace=True) df.to_csv ('data_pricenew.csv') # read the new csv file # In [26]: df = pd.read_csv (' data_pricenew.csv') df.head () # set the first column index column # In [27]: df = pd.read_csv ('data_pricenew.csv' Index_col=0) df.head () # rename column # In [28]: df.columns= ['NewPrices'] df.head () # Save as csv file Does not include column name # In [29]: df.to_csv ('data_pricenew2.csv',header=False) # In [30]: df = pd.read_csv (' data_pricenew2.csv',\ names= ['Date','Prices']) Index_col=0) df.head () # Save as html format file # In [31]: df.to_html ('dataprice.html') # for the file reading and saving format of pandas, see the official website address: # https://pandas.pydata.org/pandas-docs/stable/user_guide/io.html

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