We accept a wide variety of data files, including ASCII and Microsoft Excel. More info
The following file types are supported:
For best results on ASCII and Excel files:
- ASCII text files (space separated, comma separated, tab separated, and fixed length)
- Microsoft Excel files (*.xls, *.xlsx)
- SQLite files (*.sqlite)
- VOTable files (*.vot, *.xml)
- FITS files (*.fits)
- IPAC files (*.tbl)
- Numpy files (*.npy)
- HDF5 files (*.h5)
Problems with uploading?
- You may include NANs, but make sure you're consistent. If there is one string of text used consistently in a numeric column such as "nan", "---" or "unknown", it will be treated as a missing value. If there is more than one, the whole column will be treated as text. When in doubt, use "nan" for missing values, for it is case insensitive and always treated as a missing value on numeric columns.
- Make sure each row has the same number of columns. If a row has an incorrect number of columns, Filtergraph cannot determine which columns match up. Rows with incorrect columns will be ignored.
- Place a header in the first row to name each column. If a header cannot be found, the column names will be assigned as Column1, Column2, etc. You may optionally use the '#' symbol to designate a header. If you include a header, make sure the name of each column is unique, otherwise the duplicate names will be modified.
- Try saving it in a different format. You may want to open the file using a spreadsheet program such as Microsoft Excel, then save it to one of the other formats we support. If you are experienced with Python, you may use special libraries to save to the more technical file formats such as Numpy and HDF5.