Dataframe change the column with the date

[kalyn]

How to turn 'Timestamp' into a pole with a normal date like 1/14/2009? http://file.sampo.ru/w3862t/

df = pd.read_csv('temp.csv')
df

[inna]

Use the parameter. https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_csv.html :

df = pd.read_csv("temp.csv", parse_dates=["Timestamp"])

result:

In [114]: df.head()
Out[114]:
   Timestamp  F
0 2012-01-03  1
1 2012-01-06  1
2 2012-01-09  1
3 2012-01-12  1
4 2012-01-15  1
In [115]: df.dtypes

Out[115]:

Timestamp    datetime64[ns]   #  <-- NOTE!!!

F                     int64

dtype: object

---

If there is at least one line in the data where time does not indicate midnight (00:00:00Then Pandas will show both date and time:

In [116]: df = pd.read_csv("temp.csv", parse_dates=["Timestamp"])

In [117]: df.head()

Out[117]:

Timestamp  F

0 2012-01-03 21:59:00  1

1 2012-01-06 00:00:00  1

2 2012-01-09 00:00:00  1

3 2012-01-12 00:00:00  1

4 2012-01-15 00:00:00  1

The time component can be cut as follows:

In [118]: df["Timestamp"] = df["Timestamp"].dt.floor("D")

In [119]: df.head()

Out[119]:

Timestamp  F

0 2012-01-03  1

1 2012-01-06  1

2 2012-01-09  1

3 2012-01-12  1

4 2012-01-15  1

If you need to convert the date to a given format, it's done:

df["timestamp_str"] = df["Timestamp"].dt.strftime("%m/%d/%Y")

result:

In [121]: df.head()

Out[121]:

Timestamp  F timestamp_str

0 2012-01-03  1    01/03/2012

1 2012-01-06  1    01/06/2012

2 2012-01-09  1    01/09/2012

3 2012-01-12  1    01/12/2012

4 2012-01-15  1    01/15/2012

In [122]: df.dtypes

Out[122]:

Timestamp        datetime64[ns]

F                         int64

timestamp_str            object  #  <-- NOTE!!!

dtype: object

NOTE: After this transformation, you will get the lines instead of the dates and, as a consequence, you will not be able to use any function to deal with dates/time, including arithmetic dates. Usually, dates are converted to a specific format only before they are retained in text form or for display/graph.