How to view data saved with a Pandas Dataframe
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I have downloaded an Apple stock price timeseries dataset and loaded it into a
DataFrame. However, I don't see the object in Spyder's Variable Explorer. Where is it saved?
In any case, I would like to view the data.
import pandas as pd import ystockquote as ys aapl = ys.get_historical_prices("aapl", "2010-01-01", "2015-01-01") data = pd.DataFrame(aapl) >>> data <class 'pandas.core.frame.DataFrame'> Index: 6 entries, Adj Close to Volume Columns: 1258 entries, 2010-01-04 to 2014-12-31 dtypes: object(1258)
For some reason, the data doesn't display. Does the object not appearing in the Variable Explorer have anything to do with this issue?
To print the first
N rows, try:
For more information, see here.
Python Pandas DataFrame: load, edit, view data, How do you determine the data type for a data frame? Preview DataFrames with head () and tail () The DataFrame.head () function in Pandas, by default, shows you the top 5 rows of data in the DataFrame. The opposite is DataFrame.tail (), which gives you the last 5 rows. Pass in a number and Pandas will print out the specified number of rows as shown in the example below.
(Spyder dev here) Support for Pandas DataFrames was added in Spyder 2.3.1, so I suppose you are using a version older than that.
Spyder latest version is 2.3.8, so I encourage you to update to that version. It also fixes some problems with Series not showing in our Variable Explorer for Pandas 0.17.
How to get & check data types of Dataframe columns in Python , be stored. A string representing the compression to use in the output file. Steps to Select Rows from Pandas DataFrame. Step 1: Data Setup. Pandas read_csv() is an inbuilt function that is used to import the data from a CSV file and analyze that data in Python. So Step 2: Import CSV Data. Step 3: Select Rows from Pandas DataFrame. Select pandas rows using iloc property.
If you want to see the data frame variable in variable explorer Uncheck "exclude unsupported data types" in the variable explorer's option
Pandas DataFrame: to_pickle() function, Learn how to load, preview, select, rename, edit, and plot data using Python Data The Pandas DataFrame – loading, editing, and viewing data in Python After manipulation or calculations, saving your data back to CSV is the next step. Saving a Pandas Dataframe as a CSV Pandas is an open source library which is built on top of NumPy library. It allows user for fast analysis, data cleaning & preparation of data efficiently.
maybe this could work. Try adding a str method to the ur class and in that method show the data you want to show. eg
class Frame(DataFrame): def __str__(self): return self.as_matrix()
so this could show the matrix in the data explorer. this will only work if the data explorer uses the standard string representation of unknown types.
Using Pandas and Python to Explore Your Dataset – Real Python, Displaying Data Types; Showing Basics Statistics; Exploring Your Dataset Combining Multiple Datasets; Visualizing Your Pandas DataFrame; Conclusion When you execute the script, it will save the file nba_all_elo.csv in class Series: data # A pointer to where your array is stored size # The number of items in your array shape # The shape of your array dtype # How to interpret the array So when you create a view a new array object is created but (and that's important) the View's data pointer points to the original array. It could be offset but it still points
How to Check the Data Type in Pandas DataFrame, Note that initially the values under the 'Prices' column were stored as strings by placing quotes around those values. Step 3: Check the Data Type. Save DataFrame in smallest possible file size - parquet or pickle.gz (check what's better for your data) Save a very big DataFrame (10+ millions of rows) - hdf Be able to read the data on another platform (not Python) that doesn't support other formats - csv , csv.gz , check if parquet is supported
pandas.DataFrame.info, By default, this follows the pandas.options.display.memory_usage setting. DataFrame'> RangeIndex: 5 entries, 0 to 4 Data columns (total 3 columns): Hence, NumPy or pandas must be downloaded and installed in your Python interpreter. Viewing as array or DataFrame From the Variables tab of the Debug tool window. Launch the debugger session. In the Variables tab of the Debug tool window, select an array or a DataFrame. Click a link View as Array/View as DataFrame to the right.
Indexing and selecting data, Here we construct a simple time series data set to use for illustrating the indexing functionality: In : you may also use tab-completion to see the accessible columns of a DataFrame. You can also pass a name to be stored in the index:. Accessing pandas dataframe columns, rows, and cells At this point you know how to load CSV data in Python. In this lesson, you will learn how to access rows, columns, cells, and subsets of rows and columns from a pandas dataframe.
- "isn't saved in the Variable Explorer on the Python Spyder IDE", didnt get you there. Could you add some more info.
- If you run the code I put in my question and run it. The variable "data" does not show up in the Variable Explorer.
- In R/Matlab, if you create a variable. x=5;. The variable is saved in your workspace.
- the data is there just the explorer doesnt support it so, it wouldnt show it . uncheck "exclude unsupported data types". in the explorer option.
- looking for that option."exclude unsupported data types".