Convert to date using formatters parameter in pandas to_string

Question

I know there are several ways to convert a column to a date object, but what I am looking for is a way to do so while simultaneously formatting other columns. Say I have the following data frame:

import pandas as pd

url = "https://raw.github.com/pandas-dev/pandas/master/pandas/tests/data/tips.csv"
df = pd.read_csv(url)
df["date"] = list(range(42005, 42005+len(df)))

What I’m trying to achieve is the ability to print these data using some formatting, so I might do something like the following:

print(
  df
  .head(10)
  .to_string(
    formatters={"total_bill": "${:,.2f}".format, 
                "tip": "${:,.2f}".format
    }
  )
)

But I also want to format the date in this step as well. I tried looking through here for what I was looking for, but the datetime options didn’t seem like they would work in what I’m trying to do, and building a custom option is a bit outside scope for my target audience.

Is it possible to do this in a simple manner?

Asked By: tblznbits

||

Source

Answer 1

Turns out this is incredibly easy once you realize how the function actually works…

print(
    df
    .head(10)
    .to_string(
        formatters={"total_bill": "${:,.2f}".format, 
                    "tip": "${:,.2f}".format,
                    "date": lambda x: "{:%m/%d/%Y}".format(pd.to_datetime(x, unit="D"))
        }
    )
)

  total_bill   tip     sex smoker  day    time  size       date
0     $16.99 $1.01  Female     No  Sun  Dinner     2 02/08/2017
1     $10.34 $1.66    Male     No  Sun  Dinner     3 02/09/2017
2     $21.01 $3.50    Male     No  Sun  Dinner     3 02/10/2017
3     $23.68 $3.31    Male     No  Sun  Dinner     2 02/11/2017
4     $24.59 $3.61  Female     No  Sun  Dinner     4 02/12/2017
5     $25.29 $4.71    Male     No  Sun  Dinner     4 02/13/2017
6      $8.77 $2.00    Male     No  Sun  Dinner     2 02/14/2017
7     $26.88 $3.12    Male     No  Sun  Dinner     4 02/15/2017
8     $15.04 $1.96    Male     No  Sun  Dinner     2 02/16/2017
9     $14.78 $3.23    Male     No  Sun  Dinner     2 02/17/2017

Answered By: tblznbits

Convert to date using formatters parameter in pandas to_string

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