Calculate the Min in Python

Your goal

You need to calculate the minimum value in a numerical dataset in Python.

Step-by-step tutorial

There are multiple ways to do this, depending on your data representation.

List data

Python has a built-in min function for calculating the minimum value in a list:

>>> data = [3, 1, 4, 1, 5, 9, 2, 6, 5, 3]
>>> min(data)
1

Pandas DataFrame

You can calculate the min for whole DataFrame, or else just a single column. Here's how to do the whole DataFrame:

>>> import pandas as pd
>>> precip = pd.read_csv("precip-central-park.csv")
>>> precip
     YEAR   JAN   FEB   MAR   APR   MAY   JUN   JUL   AUG   SEP   OCT   NOV   DEC  ANNUAL
0    1869  2.53  6.87  4.61  1.39  4.15  4.40  3.20  1.76  2.81  6.48  2.03  5.02   45.25
1    1870  4.41  2.83  3.33  5.11  1.83  2.82  3.76  3.07  2.52  4.97  2.42  2.18   39.25
2    1871  2.07  2.72  5.54  3.03  4.04  7.05  5.57  5.60  2.34  7.50  3.56  2.24   51.26
3    1872  1.88  1.29  3.74  2.29  2.68  2.93  7.83  6.29  2.95  3.35  4.08  3.18   42.49
4    1873  5.34  3.80  2.09  4.16  3.69  1.28  4.61  9.56  3.14  2.73  4.63  2.96   47.99
..    ...   ...   ...   ...   ...   ...   ...   ...   ...   ...   ...   ...   ...     ...
146  2015  5.23  2.04  4.72  2.08  1.86  4.79  3.98  2.35  3.28  3.91  2.01  4.72   40.97
147  2016  4.41  4.40  1.17  1.61  3.75  2.60  7.02  1.97  2.79  4.15  5.41  2.89   42.17
148  2017  4.83  2.48  5.25  3.84  6.38  4.76  4.19  3.34  2.00  4.18  1.58  2.21   45.04
149  2018  2.18  5.83  5.17  5.78  3.53  3.11  7.45  8.59  6.19  3.59  7.62  6.51   65.55
150  2019  3.58  3.14  3.87  4.55  6.82  5.46  5.77  3.70  0.95  6.15  1.95  7.09   53.03

[151 rows x 14 columns]
>>> precip.min()
YEAR      1869.00
JAN          0.58
FEB          0.46
MAR          0.80
APR          0.95
MAY          0.30
JUN          0.02
JUL          0.44
AUG          0.18
SEP          0.21
OCT          0.14
NOV          0.34
DEC          0.25
ANNUAL      26.09
dtype: float64

Here's how to do a single column, based on a Pandas Series:

>>> precip["AUG"].min()
0.18