pandas数据读取
目录
前言
本人NLP研究方向，个人pandas学习笔记，供参考。
http://c.biancheng.net/pandas/
https://www.bilibili.com/video/BV1UJ411A7Fs?spm_id_from=333.999.0.0
一、pandas读取表格类型数据
csv tsv txtpd.read_csvexcelpd.read_excelmysqlpd.read_sql
二、操作
1.读取纯文本文件
读取csv文件
pandas.read_csv(filepath_or_buffer, sep=',', delimiter=None, header='infer',names=None, index_col=None, usecols=None)
import pandas as pd
df=pd.read_csv("C:/Users/Administrator/Desktop/person.csv")
print (df)
查看前几行df.head(n)查看后几行df.tail(n)查看数据形状，返回行数、列数df.shape查看列名/行名df.columns /df.index查看类型df.dtypes
读取txt文件
import pandas as pd
data = "xxx.txt"
df = pd.read_csv(data,sep="/t",header=None,names=['xx','xxx'])
2.读取xlsx格式excel文件
pd.read_excel(io, sheet_name=0, header=0, names=None, index_col=None,
usecols=None, squeeze=False,dtype=None, engine=None,
converters=None, true_values=None, false_values=None,
skiprows=None, nrows=None, na_values=None, parse_dates=False,
date_parser=None, thousands=None, comment=None, skipfooter=0,
convert_float=True, **kwds)
DataFrame.to_excel(excel_writer, sheet_name='Sheet1', na_rep='', float_format=None, columns=None, header=True, index=True, index_label=None, startrow=0, startcol=0, engine=None, merge_cells=True, encoding=None, inf_rep='inf', verbose=True, freeze_panes=None)
import pandas as pd
file = '课程目标达成.xls'
data = pd.read_excel(io=file, sheet_name='课程目标')
3.读取mysql数据表
import pymysql
conn = pymysql.connect(host='127.0.0.1',user='root',password='123456',database='teat',charset='utf8')
df = pd.read_sql("select * from crazyant_pvuv",con=conn)
Original: https://blog.csdn.net/weixin_43543074/article/details/124457907
Author: Heralili
Title: pandas数据分析——数据读取
原创文章受到原创版权保护。转载请注明出处：https://www.johngo689.com/695869/
转载文章受原作者版权保护。转载请注明原作者出处！