The following is a method for selecting rows and columns based on pandas data samples. It has a good reference value and I hope it will be helpful to everyone. Let’s take a look together
Note: The following code is written based on python3.5.0
import pandas food_info = pandas.read_csv("food_info.csv") # ------------------选取数据样本的第一行-------------------- print(food_info.loc[0]) #------------------选取数据样本的3到6行---------------------- print(food_info.loc[3:6]) #------------------head选取数据样本的前几行------------------ print(food_info.head(2)) # ------------------选取数据样本的2,5,10行,两种方法----------- # print(food_info.loc[[2,5,10]]) #方法一 two_five_ten = [2,5,10] #方法二 print(food_info.loc[two_five_ten]) # ------------------选取数据样本的NDB_No列-------------------- # ndb_col = food_info["NDB_No"] #方法一 col_name = "NDB_No" #方法二 ndb_col = food_info[col_name] print(ndb_col) # ------------------选取数据样本的多列------------------- # zinc_copper = food_info[["Zinc_(mg)", "Copper_(mg)"]] columns = ["Zinc_(mg)", "Copper_(mg)"] zinc_copper = food_info[columns] print(zinc_copper) # ---------------------综合小例子---------------------------- col_names = food_info.columns.tolist() #把所有的行转化成list print(col_names) gram_columns = [] for c in col_names: #遍历col_names,找出所有以(g)结尾的位置 if c.endswith("(g)"): gram_columns.append(c) print(gram_columns) gram_df = food_info[gram_columns] #把所有以(g)结尾的列存放到gram_df print(gram_df.head(3))
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