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pandas date

Innocent Iguana answered on May 4, 2022 Popularity 8/10 Helpfulness 4/10

answer pandas date

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pandas date

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# Way 1 : During import
df = pd.read_csv('filename.csv', parse_dates = ['date_col1', 'date_col2'])
# Way 2 : Parsing using pandas date format
df["date_col"] = pd.to_datetime(df["date_col"], 
                                format = "%Y-%m-%d %H:%M:%S",
                                errors='coerce')
# Way 3  : parsing using python date format
df["date_col"] = df["date_col"].dt.strftime("%d-%m-%Y")
# Extract month information
df["date_col"].dt.month
# Extract year information
df["date_col"].dt.year

# Resampling date
df.resample('M', on = 'date_col')['col1'].mean()
# Resampling count
df.resample('M', on = 'date_col').size()
# Add timezone in a datetime column
df['date_col'] = df['date_col'].dt.tz_localize('America/New_York', ambiguous='NaT')
# Convert to another timezone
df['date_col'] = df['date_col'].dt.tz_convert('Europe/London')

Popularity 8/10 Helpfulness 4/10 Language python

Source: Grepper

Tags: date pandas python

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Contributed on Nov 05 2023

Innocent Iguana

0 Answers Avg Quality 2/10

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complete dates pandas

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import pandas as pd

idx = pd.date_range('09-01-2013', '09-30-2013')

s = pd.Series({'09-02-2013': 2,
               '09-03-2013': 10,
               '09-06-2013': 5,
               '09-07-2013': 1})
s.index = pd.DatetimeIndex(s.index)

s = s.reindex(idx, fill_value=0)
print(s)

Popularity 9/10 Helpfulness 3/10 Language python

Source: stackoverflow.com

Tags: pandas pa

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Contributed on May 04 2022

Robson Melchiades

0 Answers Avg Quality 2/10

pandas date

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