I’m very new to PyQt and I am struggling to populate a QTableView control.
My code is the following:
def data_frame_to_ui(self, data_frame):
"""
Displays a pandas data frame into the GUI
"""
list_model = QtGui.QStandardItemModel()
i = 0
for val in data_frame.columns:
# for the list model
if i > 0:
item = QtGui.QStandardItem(val)
#item.setCheckable(True)
item.setEditable(False)
list_model.appendRow(item)
i += 1
self.ui.profilesListView.setModel(list_model)
# for the table model
table_model = QtGui.QStandardItemModel()
# set table headers
table_model.setColumnCount(data_frame.columns.size)
table_model.setHorizontalHeaderLabels(data_frame.columns.tolist())
self.ui.profileTableView.horizontalHeader().setStretchLastSection(True)
# fill table model data
for row_idx in range(10): #len(data_frame.values)
row = list()
for col_idx in range(data_frame.columns.size):
val = QtGui.QStandardItem(str(data_frame.values[row_idx][col_idx]))
row.append(val)
table_model.appendRow(row)
# set table model to table object
self.ui.profileTableView.setModel(table_model)
Actually in the code I succeed to populate a QListView, but the values I set to the QTableView are not displayed, also you can see that I truncated the rows to 10 because it takes forever to display the hundreds of rows of the data frame.
So, What is the fastest way to populate the table model from a pandas data frame?
Thanks in advance.
Answers:
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Method 1
Personally I would just create my own model class to make handling it somewhat easier.
For example:
import sys
from PyQt4 import QtCore, QtGui
Qt = QtCore.Qt
class PandasModel(QtCore.QAbstractTableModel):
def __init__(self, data, parent=None):
QtCore.QAbstractTableModel.__init__(self, parent)
self._data = data
def rowCount(self, parent=None):
return len(self._data.values)
def columnCount(self, parent=None):
return self._data.columns.size
def data(self, index, role=Qt.DisplayRole):
if index.isValid():
if role == Qt.DisplayRole:
return QtCore.QVariant(str(
self._data.iloc[index.row()][index.column()]))
return QtCore.QVariant()
if __name__ == '__main__':
application = QtGui.QApplication(sys.argv)
view = QtGui.QTableView()
model = PandasModel(your_pandas_data)
view.setModel(model)
view.show()
sys.exit(application.exec_())
Method 2
This works:
class PandasModel(QtCore.QAbstractTableModel):
"""
Class to populate a table view with a pandas dataframe
"""
def __init__(self, data, parent=None):
QtCore.QAbstractTableModel.__init__(self, parent)
self._data = data
def rowCount(self, parent=None):
return len(self._data.values)
def columnCount(self, parent=None):
return self._data.columns.size
def data(self, index, role=QtCore.Qt.DisplayRole):
if index.isValid():
if role == QtCore.Qt.DisplayRole:
return str(self._data.iloc[index.row()][index.column()])
return None
def headerData(self, col, orientation, role):
if orientation == QtCore.Qt.Horizontal and role == QtCore.Qt.DisplayRole:
return self._data.columns[col]
return None
Using it like this:
model = PandasModel(your_pandas_data_frame) your_tableview.setModel(model)
I read here to avoid QVariant() from PyQT 4.6 on.
Method 3
I’ve found all of the proposed answers painfully slow for DataFrames with 1000+ rows. What works for me blazingly fast:
class PandasModel(QtCore.QAbstractTableModel):
"""
Class to populate a table view with a pandas dataframe
"""
def __init__(self, data, parent=None):
QtCore.QAbstractTableModel.__init__(self, parent)
self._data = data
def rowCount(self, parent=None):
return self._data.shape[0]
def columnCount(self, parent=None):
return self._data.shape[1]
def data(self, index, role=QtCore.Qt.DisplayRole):
if index.isValid():
if role == QtCore.Qt.DisplayRole:
return str(self._data.iloc[index.row(), index.column()])
return None
def headerData(self, col, orientation, role):
if orientation == QtCore.Qt.Horizontal and role == QtCore.Qt.DisplayRole:
return self._data.columns[col]
return None
Method 4
Apart from using QtCore.QAbstractTableModel, one may also inherit from QtGui.QStandardItemModel. I find this way is easier to support handleChanged event emiited from QTableView.
from PyQt5 import QtCore, QtGui
class PandasModel(QtGui.QStandardItemModel):
def __init__(self, data, parent=None):
QtGui.QStandardItemModel.__init__(self, parent)
self._data = data
for row in data.values.tolist():
data_row = [ QtGui.QStandardItem("{0:.6f}".format(x)) for x in row ]
self.appendRow(data_row)
return
def rowCount(self, parent=None):
return len(self._data.values)
def columnCount(self, parent=None):
return self._data.columns.size
def headerData(self, x, orientation, role):
if orientation == QtCore.Qt.Horizontal and role == QtCore.Qt.DisplayRole:
return self._data.columns[x]
if orientation == QtCore.Qt.Vertical and role == QtCore.Qt.DisplayRole:
return self._data.index[x]
return None
Method 5
There is actually some code in pandas supporting integration with Qt.
At the time of writing this answer, the latest pandas version is 0.18.1 and you could do:
from pandas.sandbox.qtpandas import DataFrameModel, DataFrameWidget
That code seems to be coupled to PySide, however it should be relatively trivial to make it work with PyQt. Also, that code has been deprecated and the warning says that the module will be removed in the future.
Luckily they extracted that into a separated project in GitHub called pandas-qt:
https://github.com/datalyze-solutions/pandas-qt
I would try to use that before trying to roll out my own model and view implementation.
Method 6
Here is fully working copy-paste example for PyQT5
based on @Frederick Li answer with minor modifications.
from PyQt5 import QtGui, QtWidgets
from PyQt5.QtCore import Qt
import sys
import pandas as pd
class MainWindow(QtWidgets.QMainWindow):
def __init__(self, *args, obj=None, **kwargs):
super(MainWindow, self).__init__(*args, **kwargs)
self.centralwidget = QtWidgets.QWidget(self)
sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.MinimumExpanding, QtWidgets.QSizePolicy.Fixed)
self.centralwidget.setSizePolicy(sizePolicy)
self.pdtable = QtWidgets.QTableView(self.centralwidget)
sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.MinimumExpanding, QtWidgets.QSizePolicy.Fixed)
self.pdtable.setSizePolicy(sizePolicy)
dataPD = [['tom', 10.0, 180.3], ['nick', 15.0, 175.7], ['juli', 14.0, 160.6]]
df = pd.DataFrame(dataPD, columns=['Name', 'Age', 'Height'])
print(df.dtypes)
self.model = PandasTableModel(df)
self.pdtable.setModel(self.model)
self.setCentralWidget(self.centralwidget)
class PandasTableModel(QtGui.QStandardItemModel):
def __init__(self, data, parent=None):
QtGui.QStandardItemModel.__init__(self, parent)
self._data = data
for col in data.columns:
data_col = [QtGui.QStandardItem("{}".format(x)) for x in data[col].values]
self.appendColumn(data_col)
return
def rowCount(self, parent=None):
return len(self._data.values)
def columnCount(self, parent=None):
return self._data.columns.size
def headerData(self, x, orientation, role):
if orientation == Qt.Horizontal and role == Qt.DisplayRole:
return self._data.columns[x]
if orientation == Qt.Vertical and role == Qt.DisplayRole:
return self._data.index[x]
return None
if __name__ == "__main__":
app = QtWidgets.QApplication(sys.argv)
app.setStyle("Fusion")
main = MainWindow()
main.show()
main.resize(600, 400)
sys.exit(app.exec_())
Method 7
Simple and faster way to write a dataframe to QtableWidget
# Takes a df and writes it to a qtable provided. df headers become qtable headers
@staticmethod
def write_df_to_qtable(df,table):
headers = list(df)
table.setRowCount(df.shape[0])
table.setColumnCount(df.shape[1])
table.setHorizontalHeaderLabels(headers)
# getting data from df is computationally costly so convert it to array first
df_array = df.values
for row in range(df.shape[0]):
for col in range(df.shape[1]):
table.setItem(row, col, QtGui.QTableWidgetItem(str(df_array[row,col])))
All methods was sourced from stackoverflow.com or stackexchange.com, is licensed under cc by-sa 2.5, cc by-sa 3.0 and cc by-sa 4.0