Pandas数据读取与显示

import pandas as pdfood_info &＃61; pd.read_csv("D:\\test\\food_info.csv") #此处需要转义
print (type(food_info))

first_row &＃61; food_info.head() #默认是前5行
print (first_row)
first_row &＃61; food_info.head(3) #只读前3行
print("..............................................")
print (first_row)
print("..............................................")
print (food_info.columns) #每一列代表什么

NDB_No Shrt_Desc Water_(g) Energ_Kcal Protein_(g) \
0 1001 BUTTER WITH SALT 15.87 717 0.85
1 1002 BUTTER WHIPPED WITH SALT 15.87 717 0.85
2 1003 BUTTER OIL ANHYDROUS 0.24 876 0.28
3 1004 CHEESE BLUE 42.41 353 21.40
4 1005 CHEESE BRICK 41.11 371 23.24 Lipid_Tot_(g) Ash_(g) Carbohydrt_(g) Fiber_TD_(g) Sugar_Tot_(g) \
0 81.11 2.11 0.06 0.0 0.06
1 81.11 2.11 0.06 0.0 0.06
2 99.48 0.00 0.00 0.0 0.00
3 28.74 5.11 2.34 0.0 0.50
4 29.68 3.18 2.79 0.0 0.51 ... Vit_A_IU Vit_A_RAE Vit_E_(mg) Vit_D_mcg Vit_D_IU \
0 ... 2499.0 684.0 2.32 1.5 60.0
1 ... 2499.0 684.0 2.32 1.5 60.0
2 ... 3069.0 840.0 2.80 1.8 73.0
3 ... 721.0 198.0 0.25 0.5 21.0
4 ... 1080.0 292.0 0.26 0.5 22.0 Vit_K_(mcg) FA_Sat_(g) FA_Mono_(g) FA_Poly_(g) Cholestrl_(mg)
0 7.0 51.368 21.021 3.043 215.0
1 7.0 50.489 23.426 3.012 219.0
2 8.6 61.924 28.732 3.694 256.0
3 2.4 18.669 7.778 0.800 75.0
4 2.5 18.764 8.598 0.784 94.0 [5 rows x 36 columns]
..............................................NDB_No Shrt_Desc Water_(g) Energ_Kcal Protein_(g) \
0 1001 BUTTER WITH SALT 15.87 717 0.85
1 1002 BUTTER WHIPPED WITH SALT 15.87 717 0.85
2 1003 BUTTER OIL ANHYDROUS 0.24 876 0.28 Lipid_Tot_(g) Ash_(g) Carbohydrt_(g) Fiber_TD_(g) Sugar_Tot_(g) \
0 81.11 2.11 0.06 0.0 0.06
1 81.11 2.11 0.06 0.0 0.06
2 99.48 0.00 0.00 0.0 0.00 ... Vit_A_IU Vit_A_RAE Vit_E_(mg) Vit_D_mcg Vit_D_IU \
0 ... 2499.0 684.0 2.32 1.5 60.0
1 ... 2499.0 684.0 2.32 1.5 60.0
2 ... 3069.0 840.0 2.80 1.8 73.0 Vit_K_(mcg) FA_Sat_(g) FA_Mono_(g) FA_Poly_(g) Cholestrl_(mg)
0 7.0 51.368 21.021 3.043 215.0
1 7.0 50.489 23.426 3.012 219.0
2 8.6 61.924 28.732 3.694 256.0 [3 rows x 36 columns]
..............................................
Index([&＃39;NDB_No&＃39;, &＃39;Shrt_Desc&＃39;, &＃39;Water_(g)&＃39;, &＃39;Energ_Kcal&＃39;, &＃39;Protein_(g)&＃39;,&＃39;Lipid_Tot_(g)&＃39;, &＃39;Ash_(g)&＃39;, &＃39;Carbohydrt_(g)&＃39;, &＃39;Fiber_TD_(g)&＃39;,&＃39;Sugar_Tot_(g)&＃39;, &＃39;Calcium_(mg)&＃39;, &＃39;Iron_(mg)&＃39;, &＃39;Magnesium_(mg)&＃39;,&＃39;Phosphorus_(mg)&＃39;, &＃39;Potassium_(mg)&＃39;, &＃39;Sodium_(mg)&＃39;, &＃39;Zinc_(mg)&＃39;,&＃39;Copper_(mg)&＃39;, &＃39;Manganese_(mg)&＃39;, &＃39;Selenium_(mcg)&＃39;, &＃39;Vit_C_(mg)&＃39;,&＃39;Thiamin_(mg)&＃39;, &＃39;Riboflavin_(mg)&＃39;, &＃39;Niacin_(mg)&＃39;, &＃39;Vit_B6_(mg)&＃39;,&＃39;Vit_B12_(mcg)&＃39;, &＃39;Vit_A_IU&＃39;, &＃39;Vit_A_RAE&＃39;, &＃39;Vit_E_(mg)&＃39;, &＃39;Vit_D_mcg&＃39;,&＃39;Vit_D_IU&＃39;, &＃39;Vit_K_(mcg)&＃39;, &＃39;FA_Sat_(g)&＃39;, &＃39;FA_Mono_(g)&＃39;, &＃39;FA_Poly_(g)&＃39;,&＃39;Cholestrl_(mg)&＃39;],dtype&＃61;&＃39;object&＃39;)