Hi Just Markham,

I want to add +8 hours to all the existing times and save it to a new column in the DataFrame. I only figured out how to create a new column. But I don't know how to add my delta time to the new time data.

Electronically yours, Mr. Biggles

from datetime import timedelta
import pandas as pd

ufo = pd.read_csv('http://bit.ly/uforeports')

print("")
ufo['Time'] = pd.to_datetime(ufo.Time)
print(ufo)

print("")
print("_______________________________________________________________________")
print("")

print("ufo.dtypes")
print(ufo.dtypes)

print("")
print("_______________________________________________________________________")
print("")

# Add a new column with new data.

delta = timedelta(hours=-8)
# calc_utc_time = data_cell + delta

ufo['utc_time'] = ufo.Time
print(ufo)

print("")
print("_______________________________________________________________________")
print("")

print("ufo.dtypes")
print(ufo.dtypes)

print("")
print("_______________________________________________________________________")
print("")

First, thank you very much for the video! Also, your YT channel is amazing and has helped me a lot. I always recommend it!

I have found out in work that is possible to apply custom function to groupby operation in Pandas.

I added a snippet code to do it in the trick 19.

I am the one who has left a comment on your YT video with this trick \m/

Hi :wave: - couple of nitpicks:

• if you're using a regular expression in .str.replace, it's probably safer to make it a raw string;
• there's an unnecessary set of brackets in the call to pd.concat

(found via nqa pyupgrade pandas.ipynb --py36-plus --nbqa-mutate)

You've made a good video but you missed this one thing to explain. Actually the situation is in below code.

class NumpyEncoder(DjangoJSONEncoder):
    def default(self, obj):
        if isinstance(obj, np.ndarray):
            return obj.tolist()
        elif isinstance(obj, pd.Timestamp):
            return str(obj)

    return super().default(obj)

with pd.ExcelFile(default_storage.open(path)) as xls:
    sheet_names = xls.sheet_names
    sheets_df = [pd.read_excel(xls, sheet_name, header=None)
                 for sheet_name in sheet_names]
    worksheets_columns = [list(sheet_df.columns) for sheet_df in sheets_df]
    worksheets_data = [json.loads(json.dumps(
        sheet_df.fillna('').applymap(str).to_numpy(), cls=NumpyEncoder))
                       for sheet_df in sheets_df]

I need to convert pandas.Timestamp in the situation above to date only. Currently shows timestamp also.

Thanks in advance.

Hi Sensei Markham, @justmarkham

I need to save my DataFrame as Dictionary in order to push my data into my database using Flask SQLAlchemy. But even when I change the DataType for column Time from Datetime to Object. My dictionary variable still contains the text Timestamp, how can I remove this text and parenthesis characters from my dictionary?

ufo_dict_2

{0: {'City': 'Ithaca', 'Colors Reported': nan, 'Shape Reported': 'TRIANGLE', 'State': 'NY', 'Time': Timestamp('1930-06-01 22:00:00')}}

.

x13_change_DataType_for_Series.py

import pandas as pd

#_______________________________________________________________________________

ufo = pd.read_csv('http://bit.ly/uforeports')

print(ufo.head())
print("")
print(type(ufo))
print("")
print("ufo.dtypes")
print(ufo.dtypes)

print("")
print("_______________________________________________________________________")
print("")

#_______________________________________________________________________________

# Convert Time datatype from Object to Datetime.

ufo['Time'] = pd.to_datetime(ufo.Time)

print(ufo.head())
print("")
print(type(ufo))
print("")
print("ufo.dtypes")
print(ufo.dtypes)

print("")
print("_______________________________________________________________________")
print("")

#_______________________________________________________________________________

# Convert DataFrame to Dictionary.

ufo_dict_1 = ufo.to_dict('index')

print("ufo_dict_1")
print("")
print(dict(list(ufo_dict_1.items())[0:3]))
print("")
print(type(ufo_dict_1))

print("")
print("_______________________________________________________________________")
print("")

#_______________________________________________________________________________

# Convert Time datatype from Datetime to Object.

ufo['Time'] = ufo.Time.astype(object)

print(ufo.head())
print("")
print(type(ufo))
print("")
print("ufo.dtypes")
print(ufo.dtypes)

print("")
print("_______________________________________________________________________")
print("")

#_______________________________________________________________________________

# Convert DataFrame to Dictionary.

ufo_dict_2 = ufo.to_dict('index')

print("ufo_dict_2")
print("")
print(dict(list(ufo_dict_2.items())[0:3]))
print("")
print(type(ufo_dict_2))

print("")
print("_______________________________________________________________________")
print("")

Hi,

I just created my account in Github, pardon the simple question.

Is it possible to download the notebooks that you have provided in text format?

Here's the link of the one I'm looking at: http://nbviewer.jupyter.org/github/justmarkham/pandas-videos/blob/master/pandas.ipynb#25.-How-do-I-work-with-dates-and-times-in-pandas%3F-%28video%29

I'm planning to work with the notebooks without having to type the code one by one. If it's possible to do this please teach me how! Thank you!