我需要从 csv 文件制作散点图,在 x 轴上包含日期,在 y 轴上包含时间,我该如何编码



我需要创建一个散点图,其中包含 X 轴上的日期和 Y 轴上的时间。如果这很重要,日期看起来像 (4/10/2019(,时间看起来像 (23:55:00(。

我尝试了以下代码。

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

df = pd.read_csv("Crimes_-_2001_to_present.csv")
plt.scatter(df["Date_1"],df["Time_1"])
plt.xlabel('Date', fontsize=16)
plt.ylabel('Time', fontsize=16)
plt.title('Occurence of Crime in Relation to Time',fontsize=20)
plt.show()

我的错误消息:

====================== RESTART: F:scatter plot code.py ======================
Traceback (most recent call last):
  File "F:scatter plot code.py", line 6, in <module>
    df = pd.read_csv("Crimes_-_2001_to_present.csv")
  File "C:UsersAndrewAppDataLocalProgramsPythonPython37libsite-packagespandasioparsers.py", line 702, in parser_f
    return _read(filepath_or_buffer, kwds)
  File "C:UsersAndrewAppDataLocalProgramsPythonPython37libsite-packagespandasioparsers.py", line 429, in _read
    parser = TextFileReader(filepath_or_buffer, **kwds)
  File "C:UsersAndrewAppDataLocalProgramsPythonPython37libsite-packagespandasioparsers.py", line 895, in __init__
    self._make_engine(self.engine)
  File "C:UsersAndrewAppDataLocalProgramsPythonPython37libsite-packagespandasioparsers.py", line 1122, in _make_engine
    self._engine = CParserWrapper(self.f, **self.options)
  File "C:UsersAndrewAppDataLocalProgramsPythonPython37libsite-packagespandasioparsers.py", line 1853, in __init__
    self._reader = parsers.TextReader(src, **kwds)
  File "pandas_libsparsers.pyx", line 387, in pandas._libs.parsers.TextReader.__cinit__
  File "pandas_libsparsers.pyx", line 705, in pandas._libs.parsers.TextReader._setup_parser_source
FileNotFoundError: [Errno 2] File b'Crimes_-_2001_to_present.csv' does not exist: b'Crimes_-_2001_to_present.csv'

我完全迷失了,我感谢任何帮助!

我期待一个散点图。

您也可以尝试包含csv文件的完整路径。

df = pd.read_csv("THE FULL PATH TO YOUR FILE")

首先,检查您的.csv文件名是否正确;然后尝试将.csv文件"Crimes_-_2001_to_present.csv"和.py代码放在同一个文件夹中;跑;如果不确定:将.csv文件名更改为简单方式,例如"Crime2001.csv";.py文件更改方式: df = pd.read_csv(r"Crimes2001.csv") ;再跑一次,那一定没问题!

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