I have a large dataframe which has a column called Lead Rev. This column is a field of numbers such as (100000 or 5000 etc.) I want to know how to format these numbers to show commas as thousand separators. The dataset has over 200,000 rows.
Is it something like: '{:,}'.format('Lead Rev')
which gives this error:
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-182-5fe9c827d80b> in <module>()
----> 1 '{:,}'.format('Lead Rev')
ValueError: Cannot specify ',' or '_' with 's'.
To make all your floats show comma separators by default in pandas versions 0.23 through 0.25 set the following:
pd.options.display.float_format = '{:,}'.format
https://pandas.pydata.org/pandas-docs/version/0.23.4/options.html
In pandas version 1.0 this leads to some strange formatting in some cases.
df.head().style.format("{:,.0f}") (for all columns)
df.head().style.format({"col1": "{:,.0f}", "col2": "{:,.0f}"}) (per column)
You can use apply() to get the desired result. This works with floating too
import pandas as pd
series1 = pd.Series({'Value': 353254})
series2 = pd.Series({'Value': 54464.43})
series3 = pd.Series({'Value': 6381763761})
df = pd.DataFrame([series1, series2, series3])
print(df.head())
Value
0 3.532540e+05
1 5.446443e+04
2 6.381764e+09
df['Value'] = df.apply(lambda x: "{:,}".format(x['Value']), axis=1)
print(df.head())
Value
0 353,254.0
1 54,464.43
2 6,381,763,761.0