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 円参加ユーザー数: 546 5年弱前に終了

参加する

maruyama

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=10800&X-Amz-Date=20241118T153336Z&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAIP7GCBGMWPMZ42PQ

給与推定

働き方改革かな？

添付データ

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