打印 Pandas 中的特定行，列名和值行明智地使用正确的 dtype

Question

I am trying to print out a specific row in my dataframe with the column names and their respective values for that row. This is my code.

import pandas as pd
import numpy as np

df1 = pd.read_csv('mortality_inhospital_dataset1.csv')

df1 = df1.set_index('ID', inplace = False)

df1 = df1.loc[125047]

print(df1.fillna(0).to_string())

I am getting the following output:

My desired output is:

outcome: 0

age: 72

gendera: 0

BMI: 37.588179

I am not sure why the int values are coming up as floats. Is there a more efficient of presentable way to output this?

Answer 1

The default int dtype does not allow missing values ( nan ), so if one of the rows has missing values, then pandas will encode it as a float . As noted in the comment by @Epsi95, it's best to specify dtypes explicitly:

dtypes = {"age" : "Int64", "outcome": "Int64"}
cols_to_show = ['outcome', 'age', 'genders', 'BMI']

df1 = pd.read_csv('mortality_inhospital_dataset1.csv', index_col='ID')

df1 = df1.astype(dtypes)

print(df1.loc[125047, cols_to_show])