終了済み: 給与推定

給与推定により人事の赤池くんの窮地を救おう

賞金: 100,000 参加ユーザー数: 386 9ヶ月前に終了

働き方改革かな?

import numpy as np
import pandas as pd
from matplotlib import pyplot as plt
train = pd.read_csv("rawdata/train_data.csv")
test = pd.read_csv("rawdata/test_data.csv")
train.describe().T
count mean std min 25% 50% 75% max
id 21000.0 10499.500000 6062.322162 0.00000 5249.750000 10499.500000 15749.250000 20999.000000
position 21000.0 1.226857 1.224682 0.00000 0.000000 1.000000 2.000000 4.000000
age 21000.0 33.132476 10.715241 18.00000 24.000000 30.000000 42.000000 67.000000
sex 21000.0 1.498333 0.500009 1.00000 1.000000 1.000000 2.000000 2.000000
partner 21000.0 0.499333 0.500011 0.00000 0.000000 0.000000 1.000000 1.000000
num_child 21000.0 0.999667 1.417459 0.00000 0.000000 0.000000 2.000000 9.000000
education 21000.0 1.098571 1.116355 0.00000 0.000000 1.000000 2.000000 4.000000
service_length 21000.0 12.303143 10.696823 0.00000 3.000000 9.000000 21.000000 49.000000
study_time 21000.0 3.828476 3.312927 0.00000 1.000000 3.000000 6.000000 24.000000
commute 21000.0 1.059910 0.665307 0.10000 0.500000 1.100000 1.500000 4.800000
overtime 21000.0 12.126752 5.509408 0.00000 8.300000 12.100000 15.800000 31.900000
salary 21000.0 361.170391 171.618501 110.62231 225.498117 315.224583 456.927443 1098.943632
test.describe().T
count mean std min 25% 50% 75% max
id 9000.0 4499.500000 2598.220545 0.0 2249.75 4499.5 6749.25 8999.0
position 9000.0 1.188000 1.208091 0.0 0.00 1.0 2.00 4.0
age 9000.0 32.937778 10.704380 18.0 24.00 29.0 42.00 65.0
sex 9000.0 1.488889 0.499904 1.0 1.00 1.0 2.00 2.0
partner 9000.0 0.503667 0.500014 0.0 0.00 1.0 1.00 1.0
num_child 9000.0 1.001222 1.405820 0.0 0.00 0.0 2.00 8.0
education 9000.0 1.089444 1.112866 0.0 0.00 1.0 2.00 4.0
service_length 9000.0 12.141333 10.698280 0.0 3.00 8.0 21.00 47.0
study_time 9000.0 3.646333 3.290426 0.0 1.00 3.0 6.00 21.0
commute 9000.0 1.051700 0.656505 0.1 0.50 1.1 1.50 4.8
overtime 9000.0 7.301389 6.002899 0.0 2.00 6.5 11.50 29.5
bins = np.linspace(0, 32, 31)
train["overtime"].hist(bins = bins, alpha = 0.5, label = "train")
test["overtime"].hist(bins = bins, alpha = 0.5, label = "test")
plt.xlabel("overtime")
plt.ylabel("count")
plt.legend()
plt.show()

添付データ

  • overtime.ipynb?X-Amz-Expires=600&X-Amz-Date=20200921T113835Z&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAIP7GCBGMWPMZ42PQ
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