Apply a function for multiple columns in dataframe-CodePudding

I have a data frame as below with multiple columns,

| 190 | 191 | 192   | 193   | 194   | 195   | 196 | 197 | 198 | 199 | 16 | 36 | 116 | 156 | 176 | 200  | key          |
|-----|-----|-------|-------|-------|-------|-----|-----|-----|-----|----|----|-----|-----|-----|------|--------------|
| 0   | 0   | 21320 | 21301 | 22597 | 13624 | 2   | 0   | 0   | 1   | 1  | 0  | 1   | 4   | 3   | 1315 | 202205041315 |

I tried to apply a function to all columns ,other than last 7 columns (16,36,116,156,176,200,key).

Error in below code

df.iloc[:, :-7] = df.iloc[:, :-7].apply(lambda x: chr(round(x / 256))
                                                          chr(x % 256)).apply(lambda x: x[::-1])

If i do it for each column, the code works

df['190] = df['190].apply(lambda x: chr(round(x / 256))
                                                          chr(x % 256)).apply(lambda x: x[::-1])
df['191] = df['190].apply(lambda x: chr(round(x / 256))
                                                          chr(x % 256)).apply(lambda x: x[::-1])
df['192] = df['190].apply(lambda x: chr(round(x / 256))
                                                          chr(x % 256)).apply(lambda x: x[::-1])
df['193] = df['190].apply(lambda x: chr(round(x / 256))
                                                          chr(x % 256)).apply(lambda x: x[::-1])
df['194] = df['190].apply(lambda x: chr(round(x / 256))
                                                          chr(x % 256)).apply(lambda x: x[::-1])
...
...
df['199] = df['190].apply(lambda x: chr(round(x / 256))
                                                          chr(x % 256)).apply(lambda x: x[::-1])

I have multiple columns approx '200' columns in front of last 7 columns, so its difficult to manually enter for each columns

Could there be better way to do it.

Error:

    raise TypeError(f"cannot convert the series to {converter}")
TypeError: cannot convert the series to <class 'int'>

CodePudding user response：

Use DataFrame.applymap and add to first lambda function [::-1]:

df.iloc[:,:-7]=df.iloc[:,:-7].applymap(lambda x: (chr(round(x / 256))   chr(x % 256))[::-1])
print (df)

CodePudding user response：

Here's an alternative solution:

selection = df.iloc[:, :-7]
df_strings = selection.floordiv(256).applymap(chr)   selection.mod(256).applymap(chr)
print(df_strings)

  190 191 192 193 194 195 196 197 198 199
0      SH  S5  XE  58