如何转换包含 1 和 0 的数据框并将新列添加到表示 python 中整行的十六进制值的同一数据框

Question

我有一个 51 行和 464 列的数据框，列包含 1 和 0。我想要一个十六进制的编码值，如您在附图中看到的那样。

我试图使用 numpy 进行十六进制转换，但它会失败

df = pd.DataFrame(np.random.randint(0,2,size=(51, 464)))
#converting into numpy for easier shifting
a = df.values
b = a.dot(2**np.arange(a.size)[::-1])

我想将每 4 列分组以生成十六进制值，然后如果有奇数列用于 ex：463 而不是 464，则尾随的十六进制将根据需要的数量用零或零填充制作完整的十六进制值

此代码仅适用于 64 位长度，然后失败。我正在关注这个例子

关于如何做到这一点有什么建议吗？

Answer 1

这不是你想要的吗？

df.apply(lambda row: hex(int(''.join(map(str, row)), base=2)), axis=1)

将一行中的每个数字转换为字符串
加入他们，在字符串中创建一个大数字
将其转换为以 2 为底的整数（因为一行是二进制格式）
将其转换为十六进制

编辑： 以同样的方式转换每 4 块：

def hexize(row):
    hexes = '0x'
    
    row = ''.join(map(str, row))

    for i in range(0, len(row), 4):
        value = row[i:i+4]
        value = value.ljust(4, '0')  # right fill with 0
        value = hex(int(value, base=2))
        
        hexes += value[2:]
        
    return hexes

df.apply(hexize, axis=1)
hexize('011101100')  # returns '0x760'

Answer 2

给定输入数据：

ECID,T1,T2,T3,T4,T5,T6,T7,T8,T9,T10,T11,T12,T13,T14,T15,T16,T17,T18,T19,T20,T21,T22,T23,T24,T25,T26,T27,T28,T29,T30,T31,T32,T33,T34,T35,T36,T37,T38,T39,T40,T41,T42,T43,T44,T45,T46,T47,T48,T49,T50,T51
ABC123,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1
XYZ345,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
DEF789,1,0,1,0,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
434thECID,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0

这会添加一个类似于所询问内容的“已编码”列。原题第一行的例子好像F数不对：

import pandas as pd

def encode(row):
    s = ''.join(str(x) for x in row[1:])  # Create binary string
    s += '0' * (4 - len(row[1:]) % 4)     # Make length a multiple of 4 by adding zeros
    i = int(s,2)                          # convert to integer base 2
    h = hex(i).rstrip('0')                # strip trailing zeros
    return h if h != '0x' else '0x0'      # Handle special case of '0x0' stripping to '0x'
    
df = pd.read_csv('input.csv')
df['Encoded'] = df.apply(encode,axis=1)
print(df)

输出：

        ECID  T1  T2  T3  T4  T5  ...  T47  T48  T49  T50  T51          Encoded
0     ABC123   1   1   1   1   1  ...    1    1    1    1    1  0xffffffffffffe
1     XYZ345   1   0   0   0   0  ...    0    0    0    0    0              0x8
2     DEF789   1   0   1   0   1  ...    0    0    0    0    0             0xaa
3  434thECID   0   0   0   0   0  ...    0    0    0    0    0              0x0

[4 rows x 53 columns]

如何转换包含 1 和 0 的数据框并将新列添加到表示 python 中整行的十六进制值的同一数据框

how to convert a dataframe containing 1's and 0's and add a new column to the same dataframe that represents the hex value of entire row in python

python

boolean

dataframe

python-3.x

numpy-ndarray