How to Plot Unix Timestamp in Pandas and Python

In this short article we will see how to plot Unix timestamp in Pandas and Python.

To plot readable dates we will do a basic conversion of Unix timestamp to date in Pandas. To find more detailed examples visit How to Convert Unix Time to Date in Pandas

Setup

Let's create a DataFrame with Unix timestamp information:

dict = {'ts': {0: 1655822072.437469,
  1: 1655815574.333629,
  2: 1655797456.516109,
  3: 1655743965.358579,
  4: 1655712623.707739},
 'reply_count': {0: 2.0, 1: 3.0, 2: 3.0, 3: 2.0, 4: None}}

pd.DataFrame(dict)

Final data:

Step 1: Convert Unix timestamp to date

First we will convert the Unix time to Pandas datetime by:

df['date'] = pd.to_datetime(df['date'],unit='s')

The result will be timestamp:

1655822072.437469

to datetime:

DatetimeIndex(['2022-06-21 14:34:32.437469006',
               '2022-06-21 12:46:14.333628893',
               '2022-06-21 07:44:16.516108990'],
              dtype='datetime64[ns]', freq=None)

Step 2: Convert datetime to readable date

Next we will extract readable dates from the datetime in order to plot them.

We can get any date format(if needed consult with: How to Convert Unix Time to Date in Pandas.

For simplicity we will use day:

df['day'] = df['date'].dt.day

This will create new column which has day of month for a given time stamp

Step 3: Plot Unix timestamp as index

We can plot a given value for each day. In DataFrame above we have pairs of date and quantity:

2 - 2022-06-21 
3 - 2022-06-21 

To plot this information we can set the day or date column as index. Then select the column which needs to be plotted by:

df.set_index(['day'])['reply_count'].plot(title='Plot Unix time');

We can select also the type of the plot by kind='bar'.

Step 4: Group by Unix timestamp date and plot

Finally suppose we would like to get statistic per each period: day, week, month etc.

For this purpose we can convert the datetime to each time unit. We need also to group by each unit.

Finally we need to select a column and function which should be applied like:

• count()
• sum()
• mean()

df.groupby('day')['reply_count'].count().plot(kind='bar', title='Plot Unix time');