python - Amend column values according to timedelta and index -

i change data in pandas dataframe.

the data collect needs assigned step value. conditions of triggers step change time or high pressure or temperature values. cannot past first step: when row on pressure (1100 psi) , under temp (40 c), "dilution" phase.

when attempting change value with:

df.ix[(df['press'] > 1100) & (df['temp'] < 40),'proc'] = 'dilute'; 

i seem modify top 2 rows.

items[0].head() out[37]:                time       mass       temp       press        proc time                                                             00:00:00  10:58:07  21.947102  23.306101    1.830506      dilute 00:00:01  10:58:08  22.076259  23.306101   57.274142      dilute 00:00:02  10:58:09  22.094710  23.306101  196.000203  pressurize 00:00:03  10:58:10  22.113161  23.306101  293.318991  pressurize 00:00:03  10:58:10  22.094710  23.306101  361.161415  pressurize  items[0].tail() out[38]:                time       mass       temp     press        proc time                                                           00:36:12  11:34:19  18.201538  39.798763 -1.678585  pressurize 00:36:13  11:34:20  18.183087  39.719165 -1.444645  pressurize 00:36:14  11:34:21  18.183087  39.671407 -1.444645  pressurize 00:36:15  11:34:22  18.219989  39.703246 -1.444645  pressurize 00:36:16  11:34:23  18.201538  39.758964 -1.444645  pressurize 

upon further inspection, indexing seem work, giving me index expect see dilution occur...

print(df.ix[(df['press'] > 1100) & (df['temp'] < 40),'proc'].head(),                 df.ix[(df['press'] > 1100) & (df['temp'] < 40),'proc'].tail()) time 00:00:26    pressurize 00:00:27    pressurize 00:00:28    pressurize 00:00:29    pressurize 00:00:30    pressurize name: proc, dtype: object time 00:26:08    pressurize 00:26:09    pressurize 00:26:10    pressurize 00:26:11    pressurize 00:26:12    pressurize name: proc, dtype: object 

however, when applying data, first 2 values changed, , message--

futurewarning: in future, boolean array-likes handled boolean array index values[indexer] = value'

running cookbook examples give expected response.

it seems have nested index, i'm not clear on why, or how go amending this. there few layers here , searches solutions have not proved useful or provided best route clarify.

i thought reset index, , go numbers, need sort steps values , timedeltas.

the index timedelta, needed normalize number of runs launched on number of periods start runs @ same time 0 seconds. searches yield date munging , not time, hence normalizing values 0 timedelta index.

if there better way publish question, or more clarity, please ask. i'm more willing add clarity or trim. hard predict helpful info professional coder.

try

df['press'].astype('float') df['temp'].astype('float')  df['proc']  = np.where((df['press'] > 1100) & (df['temp'] < 40),'dilute', "pressurized")