A personal diary of DataFrame munging over the years.
Convert Series datatype to numeric (will error if column has non-numeric values)
(h/t @makmanalp)
Jason Crowe JasonCrowe
jlln
/ separator.py
Last active
November 9, 2023 19:59
Efficiently split Pandas Dataframe cells containing lists into multiple rows, duplicating the other column's values.
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| def splitDataFrameList(df,target_column,separator): | |
| ''' df = dataframe to split, | |
| target_column = the column containing the values to split | |
| separator = the symbol used to perform the split | |
| returns: a dataframe with each entry for the target column separated, with each element moved into a new row. | |
| The values in the other columns are duplicated across the newly divided rows. | |
| ''' | |
| def splitListToRows(row,row_accumulator,target_column,separator): | |
| split_row = row[target_column].split(separator) |
erichurst
/ US Zip Codes from 2013 Government Data
Created
December 9, 2013 23:00
All US zip codes with their corresponding latitude and longitude coordinates. Comma delimited for your database goodness. Source: http://www.census.gov/geo/maps-data/data/gazetteer.html
This file has been truncated, but you can view the full file.
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| ZIP,LAT,LNG | |
| 00601,18.180555, -66.749961 | |
| 00602,18.361945, -67.175597 | |
| 00603,18.455183, -67.119887 | |
| 00606,18.158345, -66.932911 | |
| 00610,18.295366, -67.125135 | |
| 00612,18.402253, -66.711397 | |
| 00616,18.420412, -66.671979 | |
| 00617,18.445147, -66.559696 | |
| 00622,17.991245, -67.153993 |