加载中…pandas_cut分区间操作study
(2020-02-23 00:17:07)
标签：
ubuntupythonpandas分区间 |
分类： Python |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sat Feb 22 22:09:45 2020
@author: dandelion
"""
import pandas as pd
import os
file = os.path.join(os.getcwd(), "log.csv")
data = pd.read_csv(file, header=0, sep=",")
# 区间门限
bins = [-150, -110, -100, -90, -80, -70, -30]
# 各区间的标签
label = labels = [
]
# 分区间操作
data["rsrp_range"] = pd.cut(data["OptimalAvgRSRP"], bins=bins,
labels=label, right=True)
# 新增字段查看
columns = data.columns.to_list()
print("数据表头字段清单为:\n", columns)
print("----------------------------")
# 使用聚合 groupby方式统计各区域采样点数
pdf = data.groupby(data["rsrp_range"]).agg({"rsrp_range":
"count"})
# 导出区间统计结果
pdf.to_csv(os.path.join(os.getcwd(),
"各区间采样点数by(groupby).csv"))
print("各区间采样点数by(groupby):\n", pdf)
print("---------------------")
# 使用pd.value_counts()方式统计各区间的采样点数
value_count = pd.value_counts(data["rsrp_range"],
sort=False)
print("各区间采样点数by(value_counts:\n", value_count)
"""
#代码执行结果示例:
#--------------------
各区间采样点数by(groupby):
rsrp_range
(-150,-110]
253
(-110,-100]
14
(-100,-90]
186
(-90,-80]
73
(-80,-70]
0
(-70,-30]
0
---------------------
各区间采样点数by(value_counts:
(-110,-100]
14
(-100,-90]
186
(-90,-80]
73
(-80,-70]
0
(-70,-30]
0
Name: rsrp_range, dtype: int64
"""
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