Pandas-27.文件讀取
read_csv和readtable()可以將文件中的內(nèi)容轉(zhuǎn)換為DataFrame對(duì)象：
pandas.read_csv(filepath_or_buffer, sep=',', delimiter=None, header='infer',
names=None, index_col=None, usecols=None)
以如下csv文件為例：
S.No,Name,Age,City,Salary
1,Tom,28,Toronto,20000
2,Lee,32,HongKong,3000
3,Steven,43,Bay Area,8300
4,Ram,38,Hyderabad,3900
- 直接讀?。?/li>
df=pd.read_csv("temp.csv")
print (df)
-
index_col自定義索引：
df=pd.read_csv("temp.csv",index_col=['S.No'])
print (df)
'''
Name Age City Salary
S.No
1 Tom 28 Toronto 20000
2 Lee 32 HongKong 3000
3 Steven 43 Bay Area 8300
4 Ram 38 Hyderabad 3900
'''
-
dtype指定類型：
df = pd.read_csv("temp.csv", dtype={'Salary': np.float64})
print (df.dtypes)
'''
S.No int64
Name object
Age int64
City object
Salary float64
dtype: object
'''
-
names指定標(biāo)題名稱,header指定首行
df=pd.read_csv("temp.csv", names=['a', 'b', 'c','d','e'])
print (df)
'''
a b c d e
0 S.No Name Age City Salary
1 1 Tom 28 Toronto 20000
2 2 Lee 32 HongKong 3000
3 3 Steven 43 Bay Area 8300
4 4 Ram 38 Hyderabad 3900
'''
df=pd.read_csv("temp.csv", names=['a', 'b', 'c','d','e'],header=0)
print (df)
'''
a b c d e
0 1 Tom 28 Toronto 20000
1 2 Lee 32 HongKong 3000
2 3 Steven 43 Bay Area 8300
3 4 Ram 38 Hyderabad 3900
'''
-
skiprows跳過(guò)指定的行數(shù)
df=pd.read_csv("temp.csv", skiprows=2)
print (df)
'''
2 Lee 32 HongKong 3000
0 3 Steven 43 Bay Area 8300
1 4 Ram 38 Hyderabad 3900
'''
