如何读取并计算文件中特定行中特定列的数据？

Question

######原文件在这
[](https://share.weiyun.com/3MLuaXO5
)
###### def Obesity_judge(BMI):
    if BMI<18.5:
        return("Underweight")
    if 18.5<=BMI<=24.9:
        return("Normal weight")
    if 25<=BMI<=29.9:
        return("Overweight")
    if BMI>=30:
        return("Obesity")
file = open("BMI data.txt", "r")
f = open("I am here.txt", "w")
a=file.readlines()
for i in a:
    b = i.split()
    print(b)
    if b[0]=="No.":
        f.write("{:6}\t{:6}\t{:6}\t{:6}\t{:6}\t{:6}\t{:6}\t{:8}\n".format('No.','sex','height','weight','SBP','DBP','BMI','Categories'))
    else:
        f.write("{:6}\t".format(b[0]))
        weight = float(b[3])
        height = float(b[2])
        c = height / 100
        BMI = weight / c ** 2
        d = round(BMI, 1)   #小数点1位
        if b[1]=="1":
            f.write("{:6}\t".format("Male"))
        else:
            f.write("{:6}\t".format("Female"))
        f.write("{:6}\t".format(b[2]))
        f.write("{:6}\t".format(b[3]))
        BP = b[4].split("/")
        f.write("{:6}\t".format(BP[0]))
        f.write("{:6}\t".format(BP[1]))
        f.write("{:5}\t".format(d))
        f.write("{:8}\n".format(Obesity_judge(d)))
file.close()
f.close()

想问如何将计算男生女生的分别的BMI值并做成图表

通过1和0调用I am here文件的BMI值

Answer 1

import pandas as pd
from matplotlib import pyplot as plt

def Obesity_judge(series):
    if series['BMI'] < 18.5:
        return "Underweight"
    if 18.5 <= series['BMI'] <= 24.9:
        return "Normal weight"
    if 25 <= series['BMI'] <= 29.9:
        return "Overweight"
    if series['BMI'] >= 30:
        return "Obesity"


df = pd.read_csv(dirname + '\\BMI data.txt', sep = '\t')
df['BMI'] = round(df.weight / ((df['height'] / 100) ** 2), 1)
df['Categories'] = df.apply(Obesity_judge, axis = 1)
dfMale = df[df['sex'] == '1']['BMI']
dfFemale = df[df['sex'] == '0']['BMI']
plt.rcParams['font.sans-serif'] = ['SimHei']
plt.rcParams['axes.unicode_minus'] = False

plt.title("男女生BMI值情况")
plt.xlabel('人数')
plt.ylabel('BMI值')
plt.plot(dfMale.values.tolist(), label='男生BMI')
plt.plot(dfFemale.values.tolist(), label='女生BMI')
plt.legend()
plt.show()