3.3 Python利用Pandas进行数据文件读写

本文章是3.3的内容，如果想要源代码和数据可以看以下链接：
https://download.csdn.net/download/Ahaha_biancheng/83338868

3.3 数据文件读写

3.3.1 读写CSV和TXT文件

3.3.1.1 读写CSV文件

例3-5 从students1.csv文件读出数据，保存为DataFrame对象

# 未定义行索引，自动生成
sdt = pd.read_csv('data/student1.csv') 
# 显示最后三条数据
sdt[-3:] 

	序号	性别	年龄	身高	体重	省份	成绩
2	3	male	22	180	62	FuJian	57
3	4	male	20	177	72	LiaoNing	79
4	5	male	20	172	74	ShanDong	91

# 文件中每个同学已有序号，读取时作为行索引,所以此时，序号一列为行索引
sdt = pd.read_csv('data/student1.csv', index_col=0)
sdt[3:] # 输出第三行往后

	性别	年龄	身高	体重	省份	成绩
序号
4	male	20	177	72	LiaoNing	79
5	male	20	172	74	ShanDong	91

sdt = pd.read_csv('data/student1.csv', index_col=0, header=None)
sdt[:] # 输出

	1	2	3	4	5	6
0
序号	性别	年龄	身高	体重	省份	成绩
1	male	20	170	70	LiaoNing	71
2	male	22	180	71	GuangXi	77
3	male	22	180	62	FuJian	57
4	male	20	177	72	LiaoNing	79
5	male	20	172	74	ShanDong	91

# 由于不是utf编码所以报错
# 先调整文件
utf = pd.read_csv('data/utf_student1.csv') 
utf

	序号	性别	年龄	身高	体重	省份	成绩
0	1	male	20	170	70	LiaoNing	71
1	2	male	22	180	71	GuangXi	77
2	3	male	22	180	62	FuJian	57
3	4	male	20	177	72	LiaoNing	79
4	5	male	20	172	74	ShanDong	91

3.3.1.2 读写TXT文件

# stxt = pd.read_csv('data/student2.txt')
# stxt = pd.read_csv('data/student2.txt', sep='\t')
# stxt = pd.read_csv('data/student2.txt', sep='\t', header=None)
name = ['序号','性别','年龄','身高','体重','省份','成绩']
# stxt = pd.read_csv('data/student2.txt', sep='\t', names=name)
stxt = pd.read_csv('data/student2.txt', sep='\t', names=name, index_col=0)
stxt

	性别	年龄	身高	体重	省份	成绩
序号
1	male	20	170	70	LiaoNing	71
2	male	22	180	71	GuangXi	77
3	male	22	180	62	FuJian	57
4	male	20	177	72	LiaoNing	79
5	male	20	172	74	ShanDong	91

通配符

使用详情可参考：
https://www.coolcou.com/pandas/pandas-read-write/pandas-read-txt.html

stxt = pd.read_csv('data/student2.txt', sep='\d', index_col=0, header=None)
stxt

:1: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.
  stxt = pd.read_csv('data/student2.txt', sep='\d', index_col=0, header=None)

	1	2	3	4	5	6	7	8	9	10
0
锘�	\tmale\t	NaN	\t	NaN	NaN	\t	NaN	\tLiaoNing\t	NaN	NaN
NaN	\tmale\t	NaN	\t	NaN	NaN	\t	NaN	\tGuangXi\t	NaN	NaN
NaN	\tmale\t	NaN	\t	NaN	NaN	\t	NaN	\tFuJian\t	NaN	NaN
NaN	\tmale\t	NaN	\t	NaN	NaN	\t	NaN	\tLiaoNing\t	NaN	NaN
NaN	\tmale\t	NaN	\t	NaN	NaN	\t	NaN	\tShanDong\t	NaN	NaN

3.3.1.3 保存csv文件

例3-7：新建DataFrame对象student,数据保存到out.csv文件

data = [[19,68,170],[20,65,165],[18,65,175]]
st = DataFrame(data, columns=['age', 'weight','height'])
print(st)
st.to_csv('out.csv',mode='w' )

   age  weight  height
0   19      68     170
1   20      65     165
2   18      65     175

3.3.2 读取Excel文件

从Excel文件中读取数据的函数类似CSV文件,需给出数据所在的Sheet表单名

pd.read_excel(file, sheetname, ...)

例3-8：从student3. xlsx文件名为“Group1”的页中读取数据

# 出错ImportError: Missing optional dependency 'xlrd'. Install xlrd >= 1.0.0 for 
# Excel support Use pip or conda to install xlrd. 版本问题


# stexl = pd.read_excel('data/student3.xlsx')
# skiprows=3 跳过前三行
# stexl = pd.read_excel('data/student3.xlsx', 'Group1', skiprows=3, index_col=0)
stexl = pd.read_excel('data/student3.xlsx', 'Group1', skiprows=[0,1,2,3], index_col=0)
stexl

	male	20	170	70	LiaoNing	71
1
2	male	22	180	71	GuangXi	77
3	male	22	180	62	FuJian	57
4	male	20	177	72	LiaoNing	79
5	male	20	172	74	ShanDong	91