Python-科学计算-pandas-22-按某列排序

发布于

系统：Windows 10 编辑器：JetBrains PyCharm Community Edition 2018.2.2 x64 pandas：1.1.5

  • 这个系列讲讲Python的科学计算及可视化
  • 今天讲讲pandas模块
  • 将df按某列进行排序

Part 1：场景描述

  1. 已知df1，包括6列，"time", "pos", "value1", "value2", "value3", "value4
  2. 其中value4为周次信息，想获取最新周次value1的取值
  3. 如下图，最新的周次应该为21KW36，其对应value1的取值为50

df

Part 2：逻辑

  1. 将df按照value4列进行排序
  2. 取第1行value1的取值即为所求

Part 3：代码

代码语言：javascript
复制
import pandas as pd

dict_1 = {"time": ["2019-11-02", "2019-11-03", "2019-11-04", "2019-11-05",

"2019-12-02", "2019-12-03", "2019-12-04", "2019-12-05"],

"pos": ["A", "A", "C", "D", "E", "E", "G", "H"],

"value1": [10, 20, 30, 40, 50, 50, 70, 80],

"value2": [100, 200, 300, 400, 500, 600, 700, 800],

"value3": [50, 20, 30, 90, 50, 60, 80, 80],

"value4": ['21W12', '21W10', '21W01', '21W05', '21W06', '21W36', '21W21', '21W23']}


df_1 = pd.DataFrame(dict_1, columns=["time", "pos", "value1", "value2", "value3", "value4"])

print("\n", "df_1", "\n", df_1, "\n")


df_1.sort_values(by='value4', ascending=False, inplace=True)


print("\n", "排序后df_1", "\n", df_1, "\n")


第1行第3列


val = df_1.iloc[0, 2]

remarks = "最新周value1取值：{0}".format(val)


print(remarks)

代码截图

执行结果

Part 4：部分代码解读

  1. df_1.sort_values(by='value4', ascending=False, inplace=True)，将df_1按照value4列进行排序，且排序方法为降序，ascending=False表示为降序，ascending为上升的意思
    • df_1.sort_values(by='value4', ascending=True, inplace=True)即按照升序来排序，结果如下图
  2. val = df_1.iloc[0, 2]，获取第1行第3列的取值，即value1列的取值。iloc为按照位置来取值，注意与loc的区别

升序

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