索引 2018/12/26
目录:
第1部分:csv文本文件读写
pandas 读csv文件read_csv(1.文本读写概要)https://mp.csdn.net/postedit/85289371
pandas 读csv文件read_csv(2.read_csv参数介绍)https://mp.csdn.net/postedit/85289928
pandas 读csv文件read_csv(3.dtypes指定列数据类型)https://mp.csdn.net/postedit/85290575
pandas 读csv文件read_csv(4.to_csv文本数据写)https://mp.csdn.net/postedit/85290962
pandas 读csv文件read_csv(5.文本数据读写实例)https://mp.csdn.net/postedit/85291123
pandas 读csv文件read_csv(6.命名和使用列)https://mp.csdn.net/postedit/85291430
pandas 读csv文件read_csv(7.索引)https://mp.csdn.net/postedit/85291658
pandas 读csv文件read_csv(8.方言和分隔符)https://mp.csdn.net/postedit/85291994
pandas 读csv文件read_csv(9.浮点转换和NA值)https://mp.csdn.net/postedit/85292391
pandas 读csv文件read_csv(10.注释和空行)https://mp.csdn.net/postedit/85292609
pandas 读csv文件read_csv(11.日期时间处理) https://mp.csdn.net/postedit/85292925
pandas 读csv文件read_csv(12.迭代和块)https://mp.csdn.net/postedit/85293639
pandas 读csv文件read_csv(13.read_fwf读固定宽度数据)https://mp.csdn.net/postedit/85294010
第2部分:
pandas hdf文件读写简要https://mp.csdn.net/postedit/85294299
pandas excel读写简要https://mp.csdn.net/postedit/85294545
第3部分:
python中csv模块用法tcy https://mp.csdn.net/postedit/85228189
pandas读csv文件read_csv错误解决办法7种https://mp.csdn.net/postedit/85228808
pandas to_string用法https://mp.csdn.net/postedit/85294935
# 实例1:带有“隐式”索引列的文件
data='A,B,C\n' \
'20190101,a,1,2\n' \
'20190102,b,3,4\n' \
'20190103,c,4,5' # 标题条目少于数据列数的文件
pd.read_csv(StringIO(data))# 假设第一列用作以下索引
A B C
20190101 a 1 2
20190102 b 3 4
20190103 c 4 5 # 日期未自动解析
df = pd.read_csv(StringIO(data), parse_dates=True)
df.index # DatetimeIndex(..., dtype='datetime64[ns]', freq=None)
实例2:读取多行索引
data='year,order,x,y\n' \
'2017,"A",1.2,.6\n' \
'2017,"B",1.5,.5\n' \
'2018,"A",.2,.06\n' \
'2018,"B",.7,.2\n' \
'2018,"C",.8,.3\n' \
'2019,"C",.2,.15\n' \
'2019,"D",.14,.05\n' \
'2019,"E",.5,.15' # 有两列索引的数据
df = pd.read_csv(StringIO(data), index_col=[0,1])
df = pd.read_csv(StringIO(data), index_col=['year','order']) #等价
x y
year order
2017 A 1.20 0.60
B 1.50 0.50
2018 A 0.20 0.06
B 0.70 0.20
C 0.80 0.30
2019 C 0.20 0.15
D 0.14 0.05
E 0.50 0.15
df.loc[2018]
x y
order
A 0.2 0.06
B 0.7 0.20
C 0.8 0.30
实例3:读取多列索引
data=',a,a,a,b,c,c\n' \
',ss1,ss2,ss3,ss4,ss5,ss6\n' \
'one,1,2,3,4,5,6\n' \
'two,7,8,9,10,11,12'
pd.read_csv(StringIO(data), header=[0, 1], index_col=0)
a b c
ss1 ss2 ss3 ss4 ss5 ss6
one 1 2 3 4 5 6
two 7 8 9 10 11 12