Question

我有10个CSV文件，每个CSV文件都具有相同的列数，以熊猫数据框的形式从中逐一读取数据。我希望这些数据显示在窗口中或以某种表格形式显示。而且应该就像每次数据进入新行一样。有什么建议吗？

以下是我的示例CSV文件：

像这样，有10个或更多CSV文件，我将一一读取这些文件中的数据，并希望在GUI中显示。

我的应用程序简介

我有一台在一定时间间隔后将CSV文件生成到文件夹中的机器。我正在使用Watchdog库将手表放在正在生成CSV文件的文件夹中。当我收到CSV文件时，将其读入熊猫数据框。上面提供了示例CSV文件。

只要机器正在运行，它就会继续生成CSV文件。因此，如果我想查看需要打开每个CSV文件的数据，则需要一个视图，其中在生成新的CSV文件时更新数据。

因此从技术上讲，正在读取的一个CSV文件被转换为数据框，然后插入某种表视图中。并且，当生成新的CSV文件时，该过程再次发生。但是现在，数据应保留在同一表视图的下一行中。

这是我的主文件：

import time
from watchdog.observers import Observer
from watchdog.events import PatternMatchingEventHandler
import pandas as pd
from Append_Function import append_df_to_excel
import os.path
import sys

class Watcher:
    def __init__(self, args):
        self.watch_dir = os.getcwd()
        print(args[0])
        self.directory_to_watch = os.path.join(self.watch_dir, args[1])
        self.observer = Observer()
        self.event_handler = Handler(patterns=["*.CSV"], ignore_patterns=["*.tmp"], ignore_directories=True)

    def run(self):
        self.observer.schedule(self.event_handler, self.directory_to_watch, recursive=False)
        self.observer.start()
        try:
            while True:
                time.sleep(1)
        except:
            self.observer.stop()
            print("Error")

        self.observer.join()


class Handler(PatternMatchingEventHandler):
    @staticmethod
    def on_any_event(event):
        if event.is_directory:
            return None
        elif event.event_type == 'created':
            # Take any action here when a file is first created.
            print("Received created event - %s." % event.src_path)
            df = pd.read_csv(event.src_path, header=1, index_col=0)
            append_df_to_excel(os.path.join(os.getcwd(), "myfile.xlsx"), df)
        elif event.event_type == 'modified':
            # Taken any actionc here when a file is modified.
            df = pd.read_csv(event.src_path, header=0, index_col=0)
            append_df_to_excel(os.path.join(os.getcwd(), "myfile.xlsx"), df)
            print("Received modified event - %s." % event.src_path)


if __name__ == '__main__':
    print(sys.argv)
    w = Watcher(sys.argv)
    w.run()

这是我的附加功能：

import pandas as pd
import openpyxl as ox


def append_df_to_excel(filename, df, sheet_name='Sheet1', startrow=None,
                       truncate_sheet=False,
                       **to_excel_kwargs):
    # ignore [engine] parameter if it was passed

    if 'engine' in to_excel_kwargs:
        to_excel_kwargs.pop('engine')

    writer = pd.ExcelWriter(filename, engine='openpyxl')

    # Python 2.x: define [FileNotFoundError] exception if it doesn't exist
    try:
        FileNotFoundError
    except NameError:
        FileNotFoundError = IOError

    try:
        # try to open an existing workbook
        writer.book = ox.load_workbook(filename,keep_vba=True)

        # get the last row in the existing Excel sheet
        # if it was not specified explicitly
        if startrow is None and sheet_name in writer.book.sheetnames:
            startrow = writer.book[sheet_name].max_row

        # truncate sheet
        if truncate_sheet and sheet_name in writer.book.sheetnames:
            # index of [sheet_name] sheet
            idx = writer.book.sheetnames.index(sheet_name)
            # remove [sheet_name]
            writer.book.remove(writer.book.worksheets[idx])
            # create an empty sheet [sheet_name] using old index
            writer.book.create_sheet(sheet_name, idx)

        # copy existing sheets
        writer.sheets = {ws.title: ws for ws in writer.book.worksheets}
    except FileNotFoundError:
        # file does not exist yet, we will create it
        pass

    if startrow is None:
        startrow = 0

    # write out the new sheet
    df.to_excel(writer, sheet_name, startrow=startrow, **to_excel_kwargs, header=True)

    # save the workbook
    writer.save()

Answer 1

您必须通过循环添加数据框：

import pandas as pd
from PyQt5 import QtCore, QtWidgets

class DataFrameTableWidget(QtWidgets.QTableWidget):
    def append_dataframe(self, df):
        df = df.copy()
        if df.columns.size > self.columnCount():
            self.setColumnCount(df.columns.size)
        r = self.rowCount()
        self.insertRow(r)
        for c, column in enumerate(df):
            it = QtWidgets.QTableWidgetItem(column)
            self.setItem(r, c, it)
        i = self.rowCount()
        for r, row in df.iterrows():
            self.insertRow(self.rowCount())
            for c, (column, value) in enumerate(row.iteritems()):
                it = QtWidgets.QTableWidgetItem(str(value))
                self.setItem(i+r , c, it)

if __name__ == '__main__':
    import sys
    app = QtWidgets.QApplication(sys.argv)
    import numpy as np
    w = DataFrameTableWidget()
    df = pd.DataFrame(np.random.randint(0, 100,size=(4, 4)), columns=list('ABCD'))
    w.append_dataframe(df)

    def after_show():
        df = pd.DataFrame(np.random.randint(0, 100,size=(4, 4)), columns=list('ABCD'))
        w.append_dataframe(df)
    QtCore.QTimer.singleShot(2*1000, after_show)
    w.resize(640, 480)
    w.show()
    sys.exit(app.exec_())

更新：

观察者在另一个线程上运行，因此它无法从该线程更新GUI，因此必须使用信号来传输信息：

import os
import time
import pandas as pd
from watchdog.observers import Observer
from watchdog.events import PatternMatchingEventHandler
from PyQt5 import QtCore, QtWidgets

from Append_Function import append_df_to_excel

class Emitter(QtCore.QObject):
    newDataFrameSignal = QtCore.pyqtSignal(pd.DataFrame)

class Watcher:
    def __init__(self, filename):
        self.watch_dir = os.getcwd()
        self.directory_to_watch = os.path.join(self.watch_dir, filename)
        self.emitter = Emitter()
        self.observer = Observer()
        self.event_handler = Handler(
            emitter=self.emitter,
            patterns=["*.CSV"], 
            ignore_patterns=["*.tmp"], 
            ignore_directories=True
        )

    def run(self):
        self.observer.schedule(self.event_handler, self.directory_to_watch, recursive=False)
        self.observer.start()


class Handler(PatternMatchingEventHandler):
    def __init__(self, *args, emitter=None, **kwargs):
        super(Handler, self).__init__(*args, **kwargs)
        self._emitter = emitter
    def on_any_event(self, event):
        if event.is_directory:
            return None
        elif event.event_type == 'created':
            # Take any action here when a file is first created.
            print("Received created event - %s." % event.src_path)
            df = pd.read_csv(event.src_path, header=1)
            self._emitter.newDataFrameSignal.emit(df.copy())
            df.set_index(df.columns.values.tolist()[0], inplace=True)
            append_df_to_excel(os.path.join(os.getcwd(), "myfile.xlsx"), df)
        elif event.event_type == 'modified':
            # Taken any actionc here when a file is modified.
            df = pd.read_csv(event.src_path, header=1)
            self._emitter.newDataFrameSignal.emit(df.copy())
            df.set_index(df.columns.values.tolist()[0], inplace=True)
            append_df_to_excel(os.path.join(os.getcwd(), "myfile.xlsx"), df)
            print("Received modified event - %s." % event.src_path)

class DataFrameTableWidget(QtWidgets.QTableWidget):
    @QtCore.pyqtSlot(pd.DataFrame)
    def append_dataframe(self, df):
        df = df.copy()
        if df.columns.size > self.columnCount():
            self.setColumnCount(df.columns.size)
        r = self.rowCount()
        self.insertRow(r)
        for c, column in enumerate(df):
            it = QtWidgets.QTableWidgetItem(column)
            self.setItem(r, c, it)
        i = self.rowCount()
        for r, row in df.iterrows():
            self.insertRow(self.rowCount())
            for c, (column, value) in enumerate(row.iteritems()):
                it = QtWidgets.QTableWidgetItem(str(value))
                self.setItem(i+r , c, it)

if __name__ == '__main__':
    import sys
    app = QtWidgets.QApplication(sys.argv)
    w = DataFrameTableWidget()
    w.resize(640, 480)
    w.show()
    watcher = Watcher(sys.argv[1])
    watcher.run()
    watcher.emitter.newDataFrameSignal.connect(w.append_dataframe)
    sys.exit(app.exec_())

Answer 2

您可能正在寻找：

Jupyter笔记本，能够将熊猫数据框显示为HTML格式的表格。
Jupyter实验室，其中包括一个GUI CSV viewer。
jupyter笔记本电脑的qgrid扩展名，使您可以交互式地过滤和编辑数据。

如果CSV文件具有相同的标题，则可能需要将数据连接到create one single table进行审查。

用于打印熊猫数据框的GUI

2 个答案: