# -*- coding: utf-8 -*-

# @File    : dataframe_demo.py
# @Date    : 2018-05-20

import pandas as pd
import numpy as np

# DataFrame对象
# 从二维ndarray对象创建  自动行、列索引
df = pd.DataFrame(np.arange(10).reshape(2, 5))
print(df)
"""
   0  1  2  3  4
0  0  1  2  3  4
1  5  6  7  8  9
"""

# 从一维ndarray对象字典创建

dt = {
    "one": pd.Series([1, 2, 3], index=["a", "b", "c"]),
    "two": pd.Series([5, 6, 7, 8], index=["a", "b", "c", "d"])
      }

df = pd.DataFrame(dt)
print(dt)
"""
{
    'one':
    a    1
    b    2
    c    3
    dtype: int64, 
    'two': 
    a    5
    b    6
    c    7
    d    8
    dtype: int64
}
"""

# 数据根据行列索引自动补齐
df = pd.DataFrame(dt, index=["a", "b", "c"], columns=["one", "two"])

print(df)
"""
   one  two
a    1    5
b    2    6
c    3    7
"""

# 从列表类型的字典创建
dt = {
    "one": [1, 2, 3, 4],
    "two": [5, 6, 7, 9]
      }

df = pd.DataFrame(dt, index=["a", "b", "c", "d"])
print(df)
"""
   one  two
a    1    5
b    2    6
c    3    7
d    4    9
"""

# 获取行索引
print(df.index)
# Index(['a', 'b', 'c', 'd'], dtype='object')

# 获取列索引
print(df.columns)
# Index(['one', 'two'], dtype='object')

# 获取值
print(df.values)
"""
[[1 5]
 [2 6]
 [3 7]
 [4 9]]
"""

# 获取列
print(df["one"])
"""
a    1
b    2
c    3
d    4
Name: one, dtype: int64
"""

#获取行
print(df.ix["a"])
"""
one    1
two    5
Name: a, dtype: int64
"""

# 获取某单元格的值
print(df["one"]["a"])
# 1