how to update column dataframe data?

Question

Usually, I use a list I simplify the timestamp by finding the difference between two successive values like this:

 x=[ 1552154111, 1552154115, 1552154117, 1552154120, 1552154125 
    ,1552154127, 1552154134, 1552154137]
    List_time = []
    for i in x:
        List_time.append((i + 1) - x[0])
    print(List_time)
[1, 5, 7, 10, 15, 17, 24, 27]

I need to have the same result by using the dataframe, which looks like this:

print(df['Timestamp'])

0         1552154111
1         1552154115
2         1552154117
3         1552154120
4         1552154125
5         1552154127
6         1552154134
7         1552154137

I need to replace the currect timestamp column with the expected difference. I don't know how to do that. It is the first I use a dataframe.

How could I do that please?

Peter Leimbigler · Accepted Answer · 2019-03-10 22:44:44Z

2

A potential solution that does not involve a df.apply(lambda) loop:

df['Timestamp'] = df['Timestamp'] - df['Timestamp'].iloc[0] + 1

answered Mar 10, 2019 at 22:44

Peter Leimbigler

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Comments

Igor OA · Accepted Answer · 2019-03-10 22:05:45Z

0

You can achieve it with :

first_value = df.loc[0]
new_row = df.apply(lambda x: x + 1 - first_value)

first_value represents x[0].

Usually, you can achieve element-wise operations on pandas Series with apply

answered Mar 10, 2019 at 22:05

Igor OA

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4 Comments

Sony Over a year ago

thank you but, it gives me this error: lambda x: op(x, rvalues)) TypeError: ("Can't convert 'int' object to str implicitly", 'occurred at index Timestamp')

Igor OA Over a year ago

What does first_value return? What is type(first_value)? Maybe df.loc[0] does not access your first line

Sony Over a year ago

print(first_value) and print(df['Timestamp'].loc[0]) give me both 1552154111

Igor OA Over a year ago

Is the type of first_value an int? Is it the same for all the entries in the Timestamp column?

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