Save values in for loop in data frame

Question

I try to figure out how to fix my problem with python. I am using pandas to create a data frame to save my data from a query. I want to extend this data frame with the column "TimeDiff" as you can see in the below table. The calculation of subtracting the time from the first element of time is working. My problem is how to create a new column with this calculated data with correct values.

Time                   Temperature     Humidity     Pulse  
2013-12-12 12:12:12    25              33           65     
2013-12-12 12:12:15    26              30           67     
2013-12-12 12:12:18    27              29           68     
2013-12-12 12:12:22    28              32           64     


Data frame should look like this:

Time                   Temperature     Humidity     Pulse     TimeDiff
2013-12-12 12:12:12    25              33           65        0
2013-12-12 12:12:15    26              30           67        3
2013-12-12 12:12:18    27              29           68        6
2013-12-12 12:12:22    28              32           64        10

My code for calculating the time difference and add it to the data frame looks like this:

df = pd.DataFrame( [[ij for ij in i] for i in rows] )
df.rename(columns={0: 'Time', 1: 'Temperature', 2: 'Humidity', 3: 'Pulse', 4:'MicValue'}, inplace=True); 
df = df.sort(['Time'], ascending=[1]);
sLength = len(df['Time'])

for i in range(sLength):
        diff = df['Time'][df.index[i]] - df['Time'][df.index[0]]
        totalSeconds = diff.total_seconds()
        # df = pd.DataFrame({'DateDiff': totalSeconds}, index=df.index)
        # df['Diff'] = df['Diff'].map(totalSeconds)

Executing this code will get the following result:

TimeDiff
740
740
740
740

So the code does not write the actual data into the data frame. It only writes the last element of the calculation of time in the whole column.

Ted Petrou · Accepted Answer · 2016-12-09 18:56:58Z

1

You can simply subtract the first index from the entire index.

df['TimeDiff'] = df.index - df.index[0]

And if you want to get seconds you can do

(df.index - df.index[0]).seconds

Or if you have your column use the dt accessor

df.TimeDiff.dt.seconds

answered Dec 9, 2016 at 18:56

Ted Petrou

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3 Comments

juanpa.arrivillaga Over a year ago

Oh yeah, that's much more straightforward.

Daniel Over a year ago

Okay thank you very much, by trying your code snipped i got an error message, which looks like this: TypeError: Input must be iterable!

Ted Petrou Over a year ago

Make sure column Time is the index and is a datetime object. `df.index = pd.to_datetime(df.Time)

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