从 pandas 中的红色列、绿色列和蓝色列创建十六进制列

Create Hex column from Red column, Green column & Blue column in pandas

我有一个包含 16,777,216 行的 pandas 数据框。这是介于 0 和 255 之间的三列(红色、绿色和蓝色)的所有可能组合。

我想在此数据框中添加一列,该列是该行三个值的十六进制代码。我认为像下面这样的东西是最好的解决方案:

df["Hex"] = "#{0:02x}{1:02x}{2:02x}".format(df["Red"],df["Green"],df["Blue"])

但是,您似乎无法将系列传递到字符串格式方法中。

有没有办法解决这个问题?此外,考虑到数据框相当大,这是最有效的方法吗?

您可以使用.apply,例如:

df = pd.DataFrame(np.random.randint(256, size=(10, 3)), columns=['Red', 'Green', 'Blue'])

例如:

   Red  Green  Blue
0  125    100   174
1  107    247   235
2  230    254    33
3   91    107    33
4  209    220   232
5  175     10    47
6  120     66    44
7   21    136   254
8  226    237    32
9   89     57    71

然后:

df.apply('#{Red:02X}{Green:02X}{Blue:02X}'.format_map, axis=1)

给你:

0    #7D64AE
1    #6BF7EB
2    #E6FE21
3    #5B6B21
4    #D1DCE8
5    #AF0A2F
6    #78422C
7    #1588FE
8    #E2ED20
9    #593947
dtype: object

对于 python 3.6+ 是可能的 使用非常快 f-strings:

z = zip(df['Red'], df['Blue'], df['Green'])
df["Hex"] = [f'#{R:02X}{B:02X}{G:02X}' for R,B,G in z]

对于较低版本:

df["Hex"] = ['#{0:02X}{1:02X}{2:02X}'.format(R,B,G) for R,B,G in z]

感谢@Jon 改进解决方案:

df["Hex"] = ['#{0:02X}{1:02X}{2:02X}'.format(*el) for el in z]

性能:

#10000 rows
df = pd.DataFrame(np.random.randint(256, size=(10000, 3)), columns=['Red', 'Green', 'Blue'])

In [244]: %%timeit 
     ...: z = zip(df['Red'], df['Green'], df['Blue'])
     ...: df["Hex"] = [f'#{R:02X}{B:02X}{G:02X}' for R,B,G in z]
     ...: 
12.9 ms ± 45.2 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)


In [245]: %%timeit
     ...: z = zip(df['Red'], df['Green'], df['Blue'])
     ...: df["Hex"] = ['#{0:02X}{1:02X}{2:02X}'.format(R,B,G) for R,B,G in z]
     ...: 
12.4 ms ± 1.14 ms per loop (mean ± std. dev. of 7 runs, 100 loops each)


In [246]: %%timeit
     ...: z = zip(df['Red'], df['Green'], df['Blue'])
     ...: df["Hex"] = ['#{0:02X}{1:02X}{2:02X}'.format(*el) for el in z]
     ...: 
11.3 ms ± 55 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)

In [246]: %%timeit
     ...: df["Hex"] = df.apply('#{Red:02X}{Green:02X}{Blue:02X}'.format_map, axis=1)
     ...: 
346 ms ± 42.6 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)