1、DataFrame的常用操作
1）查看DataFrame的大小
import pandas as pddf = pd.DataFrame([[10,6,7,8], [1,9,12,14], [5,8,10,6]], columns = ['a','b','c','d'])print(df.shape)
2）查看DataFrame的列名(columns)
import pandas as pddf = pd.DataFrame([[10,6,7,8], [1,9,12,14], [5,8,10,6]], columns = ['a','b','c','d'])print(df.columns)
3）查看DataFrame的行名(index)
import pandas as pddf = pd.DataFrame([[10,6,7,8], [1,9,12,14], [5,8,10,6]], columns = ['a','b','c','d'])print(df.index)
4）查看每行的数据类型
import pandas as pddf = pd.DataFrame([[10,6,7,8], [1,9,12,14], [5,8,10,6]], columns = ['a','b','c','d'])print(df.dtypes)
5）查看行列的内容
import pandas as pddf = pd.DataFrame([[10,6,7,8], [1,9,12,14], [5,8,10,6]], columns = ['a','b','c','d'])print(df)print(df.iloc[-1]) #选取DataFrame最后一行，返回的是Seriesprint(df.iloc[-1:]) #选取DataFrame最后一行，返回的是DataFrameprint(df.loc[0:1,'b':'c']) #这种用于选取行索引列索引已知print(df.iat[1,1]) #选取第二行第二列，用于已知行、列位置的选取。print(df.head(2)) #查看前两行的内容print(df.tail(2)) #查看后两行的内容print(df.loc[[df.index[0],df.index[1]]]) #通过label查看print(df.loc[[df.index[-2],df.index[-1]]])
6）查看每一列数据的整体特征
import pandas as pddf = pd.DataFrame([[10,6,7,8], [1,9,12,14], [5,8,10,6]], columns = ['a','b','c','d'])print(df.describe())
7）对DataFrame进行倒置
import pandas as pddf = pd.DataFrame([[10,6,7,8], [1,9,12,14], [5,8,10,6]], columns = ['a','b','c','d'])print(df.T)
2、DataFrame的行列运算
1）DataFrame中两列数据相加减
import pandas as pddf = pd.DataFrame([[10,6,7,8], [1,9,12,14], [5,8,10,6]], columns = ['a','b','c','d'])df['d - a'] = df['d'] - df['a']df['d + a'] = df['d'] + df['a']print(df)
2）DataFrame中两行数据相加减
import pandas as pddf = pd.DataFrame([[10,6,7,8], [1,9,12,14], [5,8,10,6]], columns = ['a','b','c','d'])print(df[df.a==10].values-df[df.a==1].values)print(df[df.a==10].values+df[df.a==1].values)
相关文档：
Python pandas.DataFrame.iloc函数方法的使用
Python pandas.DataFrame.loc函数方法的使用
Python pandas dataframe iloc 和 loc 的用法及区别
Python pandas.DataFrame.at函数方法的使用
Python pandas.DataFrame.iat函数方法的使用