How to pad leading zeros to the Time column?

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0
down vote

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Using 'df_dropped', a data frame, which has a column 'Time'.

df_dropped['Time'] = df_dropped['Time'].apply(lambda x:'{:0>4}'.format(x))

I don't understand what the '{:0>4}'.format(x)' does.
Please explain the construction of this line '{:0>4}'.format(x)'

edited Nov 14 at 13:12

asked Nov 13 at 5:15

Manideep Pullalachervu

2

What you are looking for might be answered here: stackoverflow.com/questions/4008546/…
– DMarczak
Nov 13 at 5:22

Possible duplicate of How to pad with n characters in Python
– user3287355
Nov 13 at 5:31

Explained here:- datacamp-global.slack.com/archives/C654VRAJ2/…
– Manideep Pullalachervu
2 days ago

add a comment |

up vote
0
down vote

favorite

Using 'df_dropped', a data frame, which has a column 'Time'.

df_dropped['Time'] = df_dropped['Time'].apply(lambda x:'{:0>4}'.format(x))

I don't understand what the '{:0>4}'.format(x)' does.
Please explain the construction of this line '{:0>4}'.format(x)'

edited Nov 14 at 13:12

asked Nov 13 at 5:15

Manideep Pullalachervu

2

What you are looking for might be answered here: stackoverflow.com/questions/4008546/…
– DMarczak
Nov 13 at 5:22

Possible duplicate of How to pad with n characters in Python
– user3287355
Nov 13 at 5:31

Explained here:- datacamp-global.slack.com/archives/C654VRAJ2/…
– Manideep Pullalachervu
2 days ago

add a comment |

up vote
0
down vote

favorite

Using 'df_dropped', a data frame, which has a column 'Time'.

df_dropped['Time'] = df_dropped['Time'].apply(lambda x:'{:0>4}'.format(x))

I don't understand what the '{:0>4}'.format(x)' does.
Please explain the construction of this line '{:0>4}'.format(x)'

edited Nov 14 at 13:12

asked Nov 13 at 5:15

Manideep Pullalachervu

Using 'df_dropped', a data frame, which has a column 'Time'.

df_dropped['Time'] = df_dropped['Time'].apply(lambda x:'{:0>4}'.format(x))

I don't understand what the '{:0>4}'.format(x)' does.
Please explain the construction of this line '{:0>4}'.format(x)'

python pandas dataframe data-science

edited Nov 14 at 13:12

asked Nov 13 at 5:15

Manideep Pullalachervu

edited Nov 14 at 13:12

asked Nov 13 at 5:15

Manideep Pullalachervu

edited Nov 14 at 13:12

asked Nov 13 at 5:15

Manideep Pullalachervu

asked Nov 13 at 5:15

Manideep Pullalachervu

asked Nov 13 at 5:15

Manideep Pullalachervu

2

What you are looking for might be answered here: stackoverflow.com/questions/4008546/…
– DMarczak
Nov 13 at 5:22

Possible duplicate of How to pad with n characters in Python
– user3287355
Nov 13 at 5:31

Explained here:- datacamp-global.slack.com/archives/C654VRAJ2/…
– Manideep Pullalachervu
2 days ago

add a comment |

2

What you are looking for might be answered here: stackoverflow.com/questions/4008546/…
– DMarczak
Nov 13 at 5:22

Possible duplicate of How to pad with n characters in Python
– user3287355
Nov 13 at 5:31

Explained here:- datacamp-global.slack.com/archives/C654VRAJ2/…
– Manideep Pullalachervu
2 days ago

What you are looking for might be answered here: stackoverflow.com/questions/4008546/…
– DMarczak
Nov 13 at 5:22

Possible duplicate of How to pad with n characters in Python
– user3287355
Nov 13 at 5:31

Explained here:- datacamp-global.slack.com/archives/C654VRAJ2/…
– Manideep Pullalachervu
2 days ago

add a comment |

1 Answer
1

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up vote
0
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It adds 0 character to each elements of data-frame until it reach 4 character. If the element is more than 4 character will do nothing.
you can see below example:

import pandas as pd



df = pd.DataFrame(data=[23, "fsda", 289801, 87], columns=['Time'], index=[0, 1, 2, 3])

df['Time'] = df['Time'].apply(lambda x: '{:0>6}'.format(x))

answered Nov 13 at 14:10

saeed heidari

1644

'{:0>6}'.format(x) can you explain this bit of code
– Manideep Pullalachervu
Nov 14 at 4:44

add a comment |

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1 Answer
1

active

oldest

votes

1 Answer
1

active

oldest

votes

up vote
0
down vote

It adds 0 character to each elements of data-frame until it reach 4 character. If the element is more than 4 character will do nothing.
you can see below example:

import pandas as pd



df = pd.DataFrame(data=[23, "fsda", 289801, 87], columns=['Time'], index=[0, 1, 2, 3])

df['Time'] = df['Time'].apply(lambda x: '{:0>6}'.format(x))

answered Nov 13 at 14:10

saeed heidari

1644

'{:0>6}'.format(x) can you explain this bit of code
– Manideep Pullalachervu
Nov 14 at 4:44

add a comment |

up vote
0
down vote

It adds 0 character to each elements of data-frame until it reach 4 character. If the element is more than 4 character will do nothing.
you can see below example:

import pandas as pd



df = pd.DataFrame(data=[23, "fsda", 289801, 87], columns=['Time'], index=[0, 1, 2, 3])

df['Time'] = df['Time'].apply(lambda x: '{:0>6}'.format(x))

answered Nov 13 at 14:10

saeed heidari

1644

'{:0>6}'.format(x) can you explain this bit of code
– Manideep Pullalachervu
Nov 14 at 4:44

add a comment |

up vote
0
down vote

It adds 0 character to each elements of data-frame until it reach 4 character. If the element is more than 4 character will do nothing.
you can see below example:

import pandas as pd



df = pd.DataFrame(data=[23, "fsda", 289801, 87], columns=['Time'], index=[0, 1, 2, 3])

df['Time'] = df['Time'].apply(lambda x: '{:0>6}'.format(x))

answered Nov 13 at 14:10

saeed heidari

1644

It adds 0 character to each elements of data-frame until it reach 4 character. If the element is more than 4 character will do nothing.
you can see below example:

import pandas as pd



df = pd.DataFrame(data=[23, "fsda", 289801, 87], columns=['Time'], index=[0, 1, 2, 3])

df['Time'] = df['Time'].apply(lambda x: '{:0>6}'.format(x))

answered Nov 13 at 14:10

saeed heidari

1644

answered Nov 13 at 14:10

saeed heidari

1644

answered Nov 13 at 14:10

saeed heidari

1644

answered Nov 13 at 14:10

saeed heidari

1644

'{:0>6}'.format(x) can you explain this bit of code
– Manideep Pullalachervu
Nov 14 at 4:44

add a comment |

'{:0>6}'.format(x) can you explain this bit of code
– Manideep Pullalachervu
Nov 14 at 4:44

'{:0>6}'.format(x) can you explain this bit of code
– Manideep Pullalachervu
Nov 14 at 4:44

add a comment |

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