Pandas accidentally setting entire column, not last in row

Question

This may be a dumb question but I am a tad stuck with this. Say I have this dataframe:

   amount  amount_str  buy_order_id        id   midprice       price  
0  0.01545000  0.01545000     915692220  53424450  0.1286495  0.12947460   
0  1.65956203  1.65956203     915692330  53424458        NaN  0.12947460   
0  0.68427900  0.68427900     915692581  53424487        NaN  0.12947460   
0  0.22306417  0.22306417     915692632  53424491        NaN  0.12808629   
0  0.22306396  0.22306396     915692964  53424530        NaN  0.12808646   
0  2.31474046  2.31474046     915693081  53424535        NaN  0.12947460   
0  0.16808924  0.16808924     915694097  53424600        NaN  0.12808675   
0  5.30166589  5.30166589     915694819  53424629        NaN  0.12808710   
price_str  sell_order_id   timestamp  type  
0  0.12947460      915690988  1518045004     0  
0  0.12947460      915690988  1518045006     0  
0  0.12947460      915690988  1518045010     0  
0  0.12808629      915692647  1518045010     1  
0  0.12808646      915693012  1518045016     1  
0  0.12947460      915690988  1518045017     0  
0  0.12808675      915694117  1518045031     1  
0  0.12808710      915694862  1518045041     1

Here is my issue: each time the program gets a new order from bitstamp, it appends the values to this dataframe, and then adds the current midprice.

I could normally do that with df['midprice'] = value; however, this sets it for the entire column and not just that entry.

How would I make it so it adds it per line and not to the entire column?

Thanks!

"I could normally do that with df['midprice'] = value" this should never work as a method for appending to a dataframe. — roganjosh
– roganjosh, Commented Feb 7, 2018 at 23:18

jpp · Accepted Answer · 2018-02-07 23:22:18Z

2

Pandas specialises in vectorised calculations.

So df['midprice'] = value sets an entire series (or column) to a fixed value.

It seems like you want to amend the last midprice value only, straight after a row is added by another process. This is one way you can achieve this:

df.iloc[-1, df.columns.get_loc('midprice')] = value

answered Feb 7, 2018 at 23:22

jpp

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18 Comments

xxen0nxx Over a year ago

something like this was exactly what I was loking for, let me see if this works. I knew it had to do with one of the iloc, loc, or iat, at.

xxen0nxx Over a year ago

Is this inline btw?

jpp Over a year ago

@xxen0nxx, not sure what you mean by inline

xxen0nxx Over a year ago

hmm, im getting an error. AttributeError: 'Series' object has no attribute 'columns'

jpp Over a year ago

convention is df refers to dataframe. try it with the correct variable.

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