Python / Pandas - GUI for viewing a DataFrame or Matrix [closed]

Question

I'm using the Pandas package and it creates a DataFrame object, which is basically a labeled matrix. Often I have columns that have long string fields, or dataframes with many columns, so the simple print command doesn't work well. I've written some text output functions, but they aren't great.

What I'd really love is a simple GUI that lets me interact with a dataframe / matrix / table. Just like you would find in a SQL tool. Basically a window that has a read-only spreadsheet like view into the data. I can expand columns, page up and down through long tables, etc.

I would suspect something like this exists, but I must be Googling with the wrong terms. It would be great if it is pandas specific, but I would guess I could use any matrix-accepting tool. (BTW - I'm on Windows.)

Any pointers?

Or, conversely, if someone knows this space well and knows this probably doesn't exist, any suggestions on if there is a simple GUI framework / widget I could use to roll my own? (But since my needs are limited, I'm reluctant to have to learn a big GUI framework and do a bunch of coding for this one piece.)

Answer 1

2019 update: I'm currently working on a successor tabloo.

---

I wasn't fully satisfied with some other GUIs, so I created my own, which I'm now maintaining on Github. Example:

Apart from the basic table + plot functionality, I wanted to have a specific way to filter data:

• select a column to filter from a combo box
• write an "underscore expression" to filter on that column using arbitrary Python code. For example: _ > 0 to filter positive values only, or more complex expressions like (_ >= date(2016, 1, 1)) & (_ <= date(2016, 1, 31)) e.g. for datetime columns.

Answer 2

I use QTableWidget from PyQt to display a DataFrame. I create a QTableWidgetObject and then populate with QTableWidgetItems created with DataFrame values. Following is the snippet of code that reads a CSV file ,create a DataFrame, then display in a GUI:

df  = read_csv(filename, index_col = 0,header = 0) self.datatable = QtGui.QTableWidget(parent=self) self.datatable.setColumnCount(len(df.columns)) self.datatable.setRowCount(len(df.index)) for i in range(len(df.index)):     for j in range(len(df.columns)):         self.datatable.setItem(i,j,QtGui.QTableWidgetItem(str(df.iget_value(i, j)))) 

Update:

As this answer was quite old, it deserves an update. There are many options available now to view the dataframes in GUI.

1. As others have pointed out, Python IDEs such as Spyder come with dataframe viewers.
2. qgrid is another option for the jupyter notebook widget that renders the dataframes within the notebook.

If someone still wants to code a simple GUI to view the dataframes within Jupyter, following is the complete , minimal example using Pyqt5 .

%gui qt5  from PyQt5.QtWidgets import QWidget,QScrollArea, QTableWidget, QVBoxLayout,QTableWidgetItem import pandas as pd  win = QWidget() scroll = QScrollArea() layout = QVBoxLayout() table = QTableWidget() scroll.setWidget(table) layout.addWidget(table) win.setLayout(layout)       df = pd.DataFrame({"a" : [4 ,5, 6],"b" : [7, 8, 9],"c" : [10, 11, 12]},index = [1, 2, 3]) table.setColumnCount(len(df.columns)) table.setRowCount(len(df.index)) for i in range(len(df.index)):     for j in range(len(df.columns)):         table.setItem(i,j,QTableWidgetItem(str(df.iloc[i, j])))  win.show()