pandas DataFrame索引行列的实现

import pandas as pd
import numpy as np

index = ["a", "b", "c", "d"]
data = np.random.randint(10, size=(4, 3))
df = pd.DataFrame(data, index=index)

"""
  0 1 2
a 9 7 1
b 0 0 7
c 2 6 5
d 8 2 5
"""

df.loc["a"]
"""
0  9
1  7
2  1
Name: a, dtype: int64
"""

df.loc["b"]
"""
0  0
1  0
2  7
Name: b, dtype: int64
"""

df.loc[["a", "c"]]
"""
  0 1 2
a 9 7 1
c 2 6 5
"""

df.iloc[0]
"""
0  9
1  7
2  1
Name: a, dtype: int64
"""

df.iloc[1]
"""
0  0
1  0
2  7
Name: b, dtype: int64
"""

df.iloc[[0, 2]]
"""
  0 1 2
a 9 7 1
c 2 6 5
"""

index = [2, 3, 4, 5]
df = pd.DataFrame(data, index=index)

"""
  0 1 2
2 9 7 1
3 0 0 7
4 2 6 5
5 8 2 5
"""

df.ix[2]
"""
0  9
1  7
2  1
Name: 2, dtype: int64
"""
# 提示信息
"""
.ix is deprecated. Please use
.loc for label based indexing or
.iloc for positional indexing
"""

# 如果 index 为整数, 则不能按行索引号进行索引
df.ix[0]
"""
...
KeyError: 0
"""

import pandas as pd
import numpy as np

columns = ["i", "ii", "iii"]
data = np.random.randint(10, size=(4, 3))
df = pd.DataFrame(data, columns=columns)

"""
  i ii iii 
0 4  5  9 
1 0  3  4 
2 7  9  1 
3 8  2  3 
"""

df.i
"""
0  4
1  0
2  7
3  8
Name: i, dtype: int64
"""

df[["i"]]
"""
  i
0 4
1 0
2 7
3 8
"""

df[["i", "ii"]]
"""
  i ii
0 4  5
1 0  3
2 7  9
3 8  2
"""

index = ["a", "f", "c", "h"]
columns = ["i", "ii", "iii"]

df = pd.DataFrame(data, index=index, columns=columns)
"""
  i ii iii
a 4  5  9
f 0  3  4
c 7  9  1
h 8  2  3
"""

df.loc[["a", "f"], ["ii", "iii"]]
"""
  ii iii
a  5  9
f  3  4
"""

df.loc["a":"c", "ii":"iii"]
"""
  ii iii
a  5  9
f  3  4
c  9  1
"""

df.iloc[[0, 1], [1, 2]]
"""
  ii iii
a  5  9
f  3  4
"""

df.iloc[:3, 1:3]
"""
  ii iii
a  5  9
f  3  4
c  9  1
"""

df.ix["a":"c", "i":"iii"]
df.ix["a":"c", 1:3]
df.ix[:3, 1:3]