Pandas数据结构DataFrame

DataFrame

1、DataFrame是一个表格型的数据结构

• 每列可以是不同的值类型（数值、字符串、布尔值等）
• 既有行索引index,也有列索引columns
• 可以被看做由Series组成的字典

import pandas as pd

data={
        'state':['Ohio','Ohio','Ohio','Nevada','Nevada'],
        'year':[2000,2001,2002,2001,2002],
        'pop':[1.5,1.7,3.6,2.4,2.9]
    }
df = pd.DataFrame(data)
print(df) #运行结果如下截图

a = df.dtypes
print(a)
#state     object
#year       int64
#pop      float64
#dtype: object

b = df.columns
print(b)
#Index(['state', 'year', 'pop'], dtype='object')
c = df.index
print(c)

2、从DataFrame中查询出Series

• 如果只查询一行、一列，返回的是pd.Series
• 如果查询多行、多列，返回的是pd.DataFrame
  查询列

import pandas as pd

data={
        'state':['Ohio','Ohio','Ohio','Nevada','Nevada'],
        'year':[2000,2001,2002,2001,2002],
        'pop':[1.5,1.7,3.6,2.4,2.9]
    }
df = pd.DataFrame(data)

#查询一列，结果是一个pd.Series
a = df["year"]
print(a,type(a))
#0    2000
#1    2001
#2    2002
#3    2001
#4    2002
#Name: year, dtype: int64 <class 'pandas.core.series.Series'>

#查询d多列，结果是一个pd.DataFrame
b = df[["year","pop"]]
print(b,type(b))
# year  pop
#0  2000  1.5
#1  2001  1.7
#2  2002  3.6
#3  2001  2.4
#4  2002  2.9 <class 'pandas.core.frame.DataFrame'>

查询行

import pandas as pd

data={
        'state':['Ohio','Ohio','Ohio','Nevada','Nevada'],
        'year':[2000,2001,2002,2001,2002],
        'pop':[1.5,1.7,3.6,2.4,2.9]
    }
df = pd.DataFrame(data)

# 查询单行
d = df.loc[0]
print(d,type(d))
#state    Ohio
#year     2000
#pop       1.5
#Name: 0, dtype: object <class 'pandas.core.series.Series'>

# 查询多行
e = df.loc[1:3]
print(e,type(e))
#state  year  pop
#1    Ohio  2001  1.7
#2    Ohio  2002  3.6
#3  Nevada  2001  2.4 
#<class 'pandas.core.frame.DataFrame'>