Read csv with dd.mm.yyyy in Python and Pandas

Question

I am reading a csv file with German date format. Seems like it worked ok in this post:

Picking dates from an imported CSV with pandas/python

However, it seems like in my case the date is not recognized as such. I could not find any wrong string in the test file.

import pandas as pd
import numpy as np


%matplotlib inline
import matplotlib.pyplot as plt

from matplotlib import style
from pandas import DataFrame

style.use('ggplot')

df = pd.read_csv('testdata.csv', dayfirst=True, parse_dates=True)
df[:5]

This results in:

So, the Column with the dates is not recognized as such. What am I doing wrong here? Or is this date format simply not compatible?

• OSX 10.10.3
• Anaconda conda 3.13.0
• Python 3.4.3-0
• iPython notebook 3.1.0

Answer 1

If you use parse_dates=True then read_csv tries to parse the index as a date. Therefore, you would also need to declare the first column as the index with index_col=[0]:

In [216]: pd.read_csv('testdata.csv', dayfirst=True, parse_dates=True, index_col=[0])
Out[216]: 
            morgens  mittags  abends
Datum                               
2015-03-16      382      452     202
2015-03-17      288      467     192

Alternatively, if you don't want the Datum column to be an index, you could use parse_dates=[0] to explicitly tell read_csv to parse the first column as dates:

In [217]: pd.read_csv('testdata.csv', dayfirst=True, parse_dates=[0])
Out[217]: 
       Datum  morgens  mittags  abends
0 2015-03-16      382      452     202
1 2015-03-17      288      467     192

---

Under the hood read_csv uses dateutil.parser.parse to parse date strings:

In [218]: import dateutil.parser as DP

In [221]: DP.parse('16.03.2015', dayfirst=True)
Out[221]: datetime.datetime(2015, 3, 16, 0, 0)

Since dateutil.parser has no trouble parsing date strings in DD.MM.YYYY format, you don't have to declare a custom date parser here.