Pandas DataFrame 获得行列索引与loc切片

import pandas as pd
import numpy as np

my_df = pd.DataFrame(data=np.arange(50).reshape(10,5),  # 10*5的矩阵
             index=list("abcdefghij"),  # 行索引
             columns=list("ABCDE"))  # 列索引
print("my_df\n",my_df)

# 行索引
print("my_df.index\n",my_df.index)
# 列索引
print("my_df.columns\n",my_df.columns)
# 数据
print("my_df.values\n",my_df.values)

# a行 A列的单个数据
print("my_df.loc[\"a\",\"A\"]\n",my_df.loc["a","A"])
# a行
print("my_df.loc[\"a\",:]\n",my_df.loc["a",:])
# A列
print("my_df.loc[:,\"A\"]\n",my_df.loc[:,"A"])

my_df
     A   B   C   D   E
a   0   1   2   3   4
b   5   6   7   8   9
c  10  11  12  13  14
d  15  16  17  18  19
e  20  21  22  23  24
f  25  26  27  28  29
g  30  31  32  33  34
h  35  36  37  38  39
i  40  41  42  43  44
j  45  46  47  48  49
my_df.index
 Index(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j'], dtype='object')
my_df.columns
 Index(['A', 'B', 'C', 'D', 'E'], dtype='object')
my_df.values
 [[ 0  1  2  3  4]
 [ 5  6  7  8  9]
 [10 11 12 13 14]
 [15 16 17 18 19]
 [20 21 22 23 24]
 [25 26 27 28 29]
 [30 31 32 33 34]
 [35 36 37 38 39]
 [40 41 42 43 44]
 [45 46 47 48 49]]
my_df.loc["a","A"]
 0
my_df.loc["a",:]
 A    0
B    1
C    2
D    3
E    4
Name: a, dtype: int64
my_df.loc[:,"A"]
 a     0
b     5
c    10
d    15
e    20
f    25
g    30
h    35
i    40
j    45
Name: A, dtype: int64