数据可视化 第2章

第2章 过滤数据

1.transform_date函数把utc格式时间转换为QDateTime类型

def transform_date(utc, timezone=None):
    utc_fmt = "yyyy-MM-ddTHH:mm:ss.zzzZ"
    new_date = QDateTime().fromString(utc, utc_fmt)
#    print (new_date.toString(utc_fmt))
    if timezone:
        new_date.setTimeZone(timezone)

    return new_date

2.drop函数过滤数据,mag<0的行都被删除

#移除错误的mag
    df = df.drop(df[df.mag < 0].index)
    magnitudes = df["mag"]

3.创建本地时区

#本地时区
    timezone = QTimeZone(b"Asia/Beijing")

4.apply方法能支持lambda表达式,能把函数应用到每行数据上,我们提取time列数据,转换为QDateTime类型

#将时间戳转换为本地时区
    times = df["time"].apply(lambda x: transform_date(x, timezone))

5.完整代码

# This Python file uses the following encoding: utf-8
import sys, argparse
import pandas as pd
from PySide2.QtCore import QDateTime, QTimeZone


def transform_date(utc, timezone=None):
    utc_fmt = "yyyy-MM-ddTHH:mm:ss.zzzZ"
    new_date = QDateTime().fromString(utc, utc_fmt)
#    print (new_date.toString(utc_fmt))
    if timezone:
        new_date.setTimeZone(timezone)

    return new_date

def read_data(fname):
    df = pd.read_csv(fname)

    #移除错误的mag
    df = df.drop(df[df.mag < 0].index)
    magnitudes = df["mag"]

    #本地时区
    timezone = QTimeZone(b"Asia/Beijing")

    #将时间戳转换为本地时区
    times = df["time"].apply(lambda x: transform_date(x, timezone))

    return times, magnitudes


if __name__ == "__main__":
    options = argparse.ArgumentParser()
    options.description = "过滤csv信息"
    options.add_argument("-f", "--file", type=str, required=True, help="CSV文件路径")
    args = options.parse_args()
    data = read_data(args.file)
    print (data)

6.控制台输出log

(0     PySide2.QtCore.QDateTime(2019, 7, 24, 9, 18, 4...
1     PySide2.QtCore.QDateTime(2019, 7, 24, 9, 10, 1...
2     PySide2.QtCore.QDateTime(2019, 7, 24, 9, 7, 3,...
3     PySide2.QtCore.QDateTime(2019, 7, 24, 9, 6, 4,...
4     PySide2.QtCore.QDateTime(2019, 7, 24, 9, 5, 43...
5     PySide2.QtCore.QDateTime(2019, 7, 24, 9, 4, 57...
6     PySide2.QtCore.QDateTime(2019, 7, 24, 9, 4, 27...
7     PySide2.QtCore.QDateTime(2019, 7, 24, 9, 1, 27...
8     PySide2.QtCore.QDateTime(2019, 7, 24, 8, 54, 5...
9     PySide2.QtCore.QDateTime(2019, 7, 24, 8, 54, 1...
10    PySide2.QtCore.QDateTime(2019, 7, 24, 8, 53, 2...
11    PySide2.QtCore.QDateTime(2019, 7, 24, 8, 52, 2...
12    PySide2.QtCore.QDateTime(2019, 7, 24, 8, 50, 1...
13    PySide2.QtCore.QDateTime(2019, 7, 24, 8, 49, 1...
14    PySide2.QtCore.QDateTime(2019, 7, 24, 8, 48, 4...
15    PySide2.QtCore.QDateTime(2019, 7, 24, 8, 47, 3...
16    PySide2.QtCore.QDateTime(2019, 7, 24, 8, 46, 5...
17    PySide2.QtCore.QDateTime(2019, 7, 24, 8, 44, 5...
18    PySide2.QtCore.QDateTime(2019, 7, 24, 8, 44, 0...
Name: time, dtype: object, 0     1.37
1     0.49
2     1.43
3     2.73
4     2.04
5     1.44
6     1.23
7     0.75
8     1.22
9     1.20
10    0.92
11    1.67
12    1.50
13    1.20
14    1.02
15    1.51
16    1.41
17    0.87
18    0.91
Name: mag, dtype: float64)
posted @ 2021-11-01 14:56  踏月清风  阅读(8)  评论(0编辑  收藏  举报