date parser python pandas code example

Example 1: date parser python pandas

mydateparser = lambda x: pd.datetime.strptime(x, "%Y %m %d %H:%M:%S")
df = pd.read_csv("file.csv", sep='\t', names=['date_column', 'other_column'], parse_dates=['date_column'], date_parser=mydateparser)

Example 2: date parser python pandas

format='%d-%b-%Y'

Example 3: date parser python pandas

import pandas as pd

values = {'dates':  ['02-Sep-2019','13-Sep-2019','21-Sep-2019'],
          'status': ['Opened','Opened','Closed']
          }

df = pd.DataFrame(values, columns = ['dates','status'])

df['dates'] = pd.to_datetime(df['dates'], format='%d-%b-%Y')

print (df)
print (df.dtypes)

Example 4: date parser python pandas

import pandas as pd

values = {'dates':  ['20190902093000','20190913093000','20190921200000'],
          'status': ['Opened','Opened','Closed']
          }

df = pd.DataFrame(values, columns = ['dates','status'])

df['dates'] = pd.to_datetime(df['dates'], format='%Y%m%d%H%M%S')

print (df)
print (df.dtypes)

Example 5: date parser python pandas

format='%d%m%Y'

Example 6: date parser python pandas

import pandas as pd

values = {'dates':  ['20190902','20190913','20190921'],
          'status': ['Opened','Opened','Closed']
          }

df = pd.DataFrame(values, columns = ['dates','status'])

df['dates'] = pd.to_datetime(df['dates'], format='%Y%m%d')

print (df)
print (df.dtypes)

Example 7: date parser python pandas

import pandas as pd

values = {'dates':  ['02092019','13092019','21092019'],
          'status': ['Opened','Opened','Closed']
          }

df = pd.DataFrame(values, columns = ['dates','status'])

df['dates'] = pd.to_datetime(df['dates'], format='%d%m%Y')

print (df)
print (df.dtypes)

Example 8: date parser python pandas

df['DataFrame Column'] = pd.to_datetime(df['DataFrame Column'], format=specify your format)

Example 9: date parser python pandas

format='%Y%m%d%H%M%S'

Example 10: date parser python pandas

import pandas as pd

values = {'dates':  ['20190902','20190913','20190921'],
          'status': ['Opened','Opened','Closed']
          }

df = pd.DataFrame(values, columns = ['dates','status'])

print (df)
print (df.dtypes)