import pandas as pd
df = pd.read_csv("001_12ib_2025m12_20260211-232655.csv",delimiter = ';')

# show the first rows
df.head()

df.info()

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 84 entries, 0 to 83
Data columns (total 5 columns):
 #   Column                                                               Non-Null Count  Dtype 
---  ------                                                               --------------  ----- 
 0   Month                                                                84 non-null     object
 1   Number of passengers                                                 84 non-null     int64 
 2   Freight and mail total, tonne                                        84 non-null     int64 
 3   Number of passengers, cumulative from the beginning of the year      84 non-null     int64 
 4   Freight and mail, cumulative from the beginning of the year, tonnes  84 non-null     int64 
dtypes: int64(4), object(1)
memory usage: 3.4+ KB

# define the columns of interest, those with numbers
columns = ["Number of passengers","Freight and mail total, tonne","Number of passengers, cumulative from the beginning of the year","Freight and mail, cumulative from the beginning of the year, tonnes"]

# normalizing the columns so that the values are scaled between 0.0 and 1.0
df[columns] = (df[columns] - df[columns].min()) / (df[columns].max() - df[columns].min())

df[columns].describe().round(2)

df[columns].corr()

df[columns].plot(figsize=(12, 6))

<Axes: >

# export it to a PureData friendly format
df[columns].to_csv("passengers",sep=" ",header=False,lineterminator=";\n")

	Month	Number of passengers	Freight and mail total, tonne	Number of passengers, cumulative from the beginning of the year	Freight and mail, cumulative from the beginning of the year, tonnes
0	2019M01	1969169	16265	1969169	16265
1	2019M02	1951842	14872	3921011	31136
2	2019M03	2203647	18561	6124658	49698
3	2019M04	2135867	18412	8260525	68110
4	2019M05	2269401	20031	10529926	88141

	Number of passengers	Freight and mail total, tonne	Number of passengers, cumulative from the beginning of the year	Freight and mail, cumulative from the beginning of the year, tonnes
count	84.00	84.00	84.00	84.00
mean	0.56	0.51	0.32	0.40
std	0.29	0.18	0.24	0.25
min	0.00	0.00	0.00	0.00
25%	0.36	0.43	0.14	0.19
50%	0.65	0.50	0.24	0.38
75%	0.74	0.58	0.49	0.59
max	1.00	1.00	1.00	1.00

	Number of passengers	Freight and mail total, tonne	Number of passengers, cumulative from the beginning of the year	Freight and mail, cumulative from the beginning of the year, tonnes
Number of passengers	1.000000	0.642697	0.592027	0.239162
Freight and mail total, tonne	0.642697	1.000000	0.426754	0.360766
Number of passengers, cumulative from the beginning of the year	0.592027	0.426754	1.000000	0.835316
Freight and mail, cumulative from the beginning of the year, tonnes	0.239162	0.360766	0.835316	1.000000