DataFrame读取CSV文件

最新推荐文章于 2025-06-18 16:56:47 发布

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最新推荐文章于 2025-06-18 16:56:47 发布

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CC 4.0 BY-SA版权

文章标签： python 开发工具数据结构与算法

原文链接：http://www.cnblogs.com/rhyswang/p/8327574.html

本文介绍了使用Python的Pandas库来读取不同格式的CSV文件的方法，包括使用不同的分隔符、设置特定行作为表头、指定列名、设置索引列、跳过某些行及处理缺失值等。

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读取csv的代码：

print pd.read_csv("ex1.csv")

print "\n"
print "Can also use read table with a specific separator"
print pd.read_table("ex1.csv",sep=',')

print "\n"
print "Read a csv and define a row as its header"
print pd.read_csv("ex2.csv",header=None)
print "###"
print pd.read_csv("ex2.csv",header=1)


print "\n"
print 'Set names for the columns'
name=['wang','li','zhao','qian','sun']
print pd.read_csv('ex2.csv',names=name)

print "\n"
print 'Set names for the columns and user a column as the index'
print pd.read_csv('ex2.csv',names=name,index_col='sun')

读取不规则csv到pandas

b = list(open('ex3.txt'))
print b
print 'User regex to split, s represents space,tap,new line, and so forth'
result = pd.read_table('ex3.txt',sep="\s+")
print result

print '\n'
print 'Skip rows from reading'
result1 = pd.read_table('ex3.txt',sep="\s+",skiprows=[1,3])
print result1

print '\n'
print 'We found some NaN somewhere'
csv5 = pd.read_csv('ex5.csv')
print csv5
print pd.isnull(csv5)

print '\n'
print "We treat 'foo' as a NaN"
csv5_fill = pd.read_csv('ex5.csv',na_values=["foo"])
print csv5_fill

转载于:https://www.cnblogs.com/rhyswang/p/8327574.html