CODEWITHSUNDEEP
pythonpandasdataframecsv
Janneman
Janneman

Reputation: 353

pd.read_csv shows indexes and column names but no values

I am confused: loading a csv works oke, that is: No Error and index en columnsnames show but there are no values in my DF. Downloading this csv, converting it to Excel, then load it in Pandas, convert it to csv (pd.to_csv) and load it again as csv works oke. The csv loads as a dataframe.... There must be something in this original csv that I don't understand. In fact my 'problem' is solved by all this converting. But I would like to understand what is wrong / what I have te learn.

So it would be great if someone knows what I am doing wrong here. thanks!

link = 'https://www.vektis.nl/uploads/Docs%20per%20pagina/Open%20Data%20Bestanden/2018/Vektis%20Open%20Databestand%20Zorgverzekeringswet%202018%20-%20postcode3.csv'
df = pd.read_csv(link)

df.shape
(137099, 1)

df.info() looks weird and df.describe() is empty.....

As said: convert original csv to xlsx, load that in pandas and convert is to csv gives a df, with values etc.

df2.info()
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 137099 entries, 0 to 137098
Data columns (total 28 columns):
GESLACHT                                  137098 non-null object
LEEFTIJDSKLASSE                           137098 non-null object
POSTCODE_3                                137098 non-null float64
AANTAL_BSN                                137099 non-null int64
AANTAL_VERZEKERDEJAREN                    137099 non-null float64
KOSTEN_MEDISCH_SPECIALISTISCHE_ZORG       137099 non-null float64
KOSTEN_FARMACIE                           137099 non-null float64
KOSTEN_SPECIALISTISCHE_GGZ                137099 non-null float64
KOSTEN_HUISARTS_INSCHRIJFTARIEF           137099 non-null float64
KOSTEN_HUISARTS_CONSULT                   137099 non-null float64
KOSTEN_HUISARTS_MDZ                       137099 non-null float64
KOSTEN_HUISARTS_OVERIG                    137099 non-null float64
KOSTEN_HULPMIDDELEN                       137099 non-null float64
KOSTEN_MONDZORG                           137099 non-null float64
KOSTEN_PARAMEDISCHE_ZORG_FYSIOTHERAPIE    137099 non-null float64
KOSTEN_PARAMEDISCHE_ZORG_OVERIG           137099 non-null float64
KOSTEN_ZIEKENVERVOER_ZITTEND              137099 non-null float64
KOSTEN_ZIEKENVERVOER_LIGGEND              137099 non-null float64
KOSTEN_KRAAMZORG                          137099 non-null float64
KOSTEN_VERLOSKUNDIGE_ZORG                 137099 non-null float64
KOSTEN_GENERALISTISCHE_BASIS_GGZ          137099 non-null float64
KOSTEN_LANGDURIGE_GGZ                     137099 non-null float64
KOSTEN_GRENSOVERSCHRIJDENDE_ZORG          137099 non-null float64
KOSTEN_EERSTELIJNS_ONDERSTEUNING          137099 non-null float64
KOSTEN_GERIATRISCHE_REVALIDATIEZORG       137099 non-null float64
KOSTEN_EERSTELIJNSVERBLIJF                137099 non-null float64
KOSTEN_VERPLEGING_EN_VERZORGING           137099 non-null float64
KOSTEN_OVERIG                             137099 non-null float64
dtypes: float64(25), int64(1), object(2)
memory usage: 29.3+ MB

1

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Upvotes: 0

Views: 73

Answers (1)

NYC Coder
NYC Coder

Reputation: 7594

You just need to provide a separator, ';' in your case:

link = 'https://www.vektis.nl/uploads/Docs%20per%20pagina/Open%20Data%20Bestanden/2018/Vektis%20Open%20Databestand%20Zorgverzekeringswet%202018%20-%20postcode3.csv'
df = pd.read_csv(link, sep=';')
print(df)

       GESLACHT LEEFTIJDSKLASSE  POSTCODE_3  ...  KOSTEN_EERSTELIJNSVERBLIJF  KOSTEN_VERPLEGING_EN_VERZORGING  KOSTEN_OVERIG
0           NaN             NaN         NaN  ...                    60376.04                        637668.87      496931.54
1             M               0         0.0  ...                        0.00                        121744.76         890.41
2             M               0       101.0  ...                        0.00                           565.22         154.32
3             M               0       102.0  ...                        0.00                           342.72          77.16
4             M               0       103.0  ...                        0.00                         11192.82        2498.61
...         ...             ...         ...  ...                         ...                              ...            ...
137094        V             90+       995.0  ...                    17126.82                        230642.72           0.00
137095        V             90+       996.0  ...                    15504.98                        133670.79           0.00
137096        V             90+       997.0  ...                     9608.72                        172186.49           0.00
137097        V             90+       998.0  ...                    37083.13                        733906.73        1083.82
137098        V             90+       999.0  ...                    26639.36                         99737.32           0.00

[137099 rows x 28 columns]

Upvotes: 1

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