在给定文件中查找列的数据类型，查找每列的最大值和最小值，如果是字符串，则根据长度查找最大值，最小值字符串

Question

data of a given file:

   Name     age   weight  
   John     21    78.5  
   kennedy  39    68.3   

expected output:

col_name   dtype
Name       str    max: kennedy min: john
age        int    max: 39      min: 21
weight     float  max: 78.5    min: 68.3

****can anyone help me with a solution?**

Also i tried this but don't know how to find it max, min for string, i just did for int, float .**

import pandas as pd

df=pd.read_csv(P1-UK-Bank-Customers.csv")

for col in df.select_dtypes([np.int8, np.int16, np.int32, np.int64, np.float]):

print('column: ', col)
print('max: ',df[col].max())
print('min: ',df[col].min())
print()**

Answer 1

Try something like this:

def min_mx_dtype(x):
    return pd.Series(index=['min', 'max', 'dtype'],data=[x.min(), x.max(), x.dtype])

print(df.apply(min_mx_dtype).T.reset_index())

      index   min      max    dtype
0      Name  John  kennedy   object
1       age    21       39    int64
2  weight    68.3     78.5  float64

Answer 2

You can create a dataframe from a list of dicts. Then print it out in whatever format you want. For strings, min and max would be equivalent to the first and last value in a list of string sorted in ascending order.

vals = []
for col in df.columns:
    vals.append({'col_name': col, 
                 'dtype': df[col].dtype,
                 'max': df[col].max(),
                 'min': df[col].min()})
df = pd.DataFrame(vals)

Output

  col_name    dtype      max   min
0     Name   object  kennedy  John
1      age    int64       39    21
2   weight  float64     78.5  68.3