This is a one-liner, you just need to use the axis argument for min to tell it to work across the columns rather than down: df[‘Minimum’] = df.loc[:, [‘B0’, ‘B1’, ‘B2’]].min(axis=1) If you need to use this solution for different numbers of columns, you can use a for loop or list comprehension to construct the … Read more
Option 0 Super Simple pd.concat([pd.Series(df[c].dropna().values, name=c) for c in df], axis=1) col1 col2 col3 col4 col5 col6 0 ABC1 15.0 24RA Large 345.0 US Can we handle more than one value per column? Sure we can! df.loc[2, ‘col3’] = ‘Test’ col1 col2 col3 col4 col5 col6 0 ABC1 15.0 Test Large 345.0 US 1 NaN … Read more
You’ll have to use an itemRenderer in order to accomplish this. See the following examples for more information: http://butterfliesandbugs.wordpress.com/2007/07/11/using-an-itemrenderer-to-change-the-background-of-a-datagrid-cell/ http://www.adobe.com/cfusion/communityengine/index.cfm?event=showdetails&postId=61&productId=2
For MS SQL Server: SCOPE_IDENTITY() will return you the last generated identity value within your current scope: SELECT SCOPE_IDENTITY() AS NewID
http://jsfiddle.net/PMRQ5/1/ Add vertical-align: top or vertical-align: bottom to the box, depends on what you want.
Poi has no built in sorting mechanism, though of course you are far from the first one with that need. I think you are getting in trouble because you are moving rows that you are iterating over. I have run the code above and it seems what is happening is rows are disappearing from the … Read more
new_header = df.iloc[0] #grab the first row for the header df = df[1:] #take the data less the header row df.columns = new_header #set the header row as the df header
with open(adresse,”r”) as f: reader = csv.reader(f,delimiter = “,”) data = list(reader) row_count = len(data) You are trying to read the file twice, when the file pointer has already reached the end of file after saving the data list.