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How to access pandas DataFrame datetime index using strings

Hello Guys, How are you all? Hope You all Are Fine. Today We Are Going To learn about How to access pandas DataFrame datetime index using strings in Python. So Here I am Explain to you all the possible Methods here.

Without wasting your time, Let’s start This Article.

Table of Contents

How to access pandas DataFrame datetime index using strings?

  1. How to access pandas DataFrame datetime index using strings?

    pandas is taking what's inside the [] and deciding what it should do. If it's a subset of column names, it'll return a DataFrame with those columns.

  2. access pandas DataFrame datetime index using strings

    pandas is taking what's inside the [] and deciding what it should do. If it's a subset of column names, it'll return a DataFrame with those columns.

Method 1

pandas is taking what’s inside the [] and deciding what it should do. If it’s a subset of column names, it’ll return a DataFrame with those columns. If it’s a range of index values, it’ll return a subset of those rows. What is does not handle is taking a single index value.

Two work around’s

1.Turn the argument into something pandas interprets as a range.

df['2008-01-01':'2008-01-01']

2.Use the method designed to give you this result. loc[]

df.loc['2008-01-01']

Method 2

Reversing your dataframe allows the indexing to work:

Here is your .csv datafile:

Date,PETR4,CSNA3,VALE5
2008-01-01,0.0,0.0,0.0
2008-01-02,1.0,1.0,1.0
2008-01-03,7.0,7.0,7.0

Use the following incantation to read it into a DataFrame:

>>> a = pd.read_csv('your.csv', index_col=0, parse_dates=True, infer_datetime_format=True)

Then, try to index a row:

>>> a['2008-01-01']
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/usr/local/lib/python2.7/dist-packages/pandas/core/frame.py", line 1969, in __getitem__
    return self._getitem_column(key)
  File "/usr/local/lib/python2.7/dist-packages/pandas/core/frame.py", line 1976, in _getitem_column
    return self._get_item_cache(key)
  File "/usr/local/lib/python2.7/dist-packages/pandas/core/generic.py", line 1091, in _get_item_cache
    values = self._data.get(item)
  File "/usr/local/lib/python2.7/dist-packages/pandas/core/internals.py", line 3211, in get
    loc = self.items.get_loc(item)
  File "/usr/local/lib/python2.7/dist-packages/pandas/core/index.py", line 1759, in get_loc
    return self._engine.get_loc(key)
  File "pandas/index.pyx", line 137, in pandas.index.IndexEngine.get_loc (pandas/index.c:3979)
  File "pandas/index.pyx", line 157, in pandas.index.IndexEngine.get_loc (pandas/index.c:3843)
  File "pandas/hashtable.pyx", line 668, in pandas.hashtable.PyObjectHashTable.get_item (pandas/hashtable.c:12265)
  File "pandas/hashtable.pyx", line 676, in pandas.hashtable.PyObjectHashTable.get_item (pandas/hashtable.c:12216)
KeyError: '2008-01-01'

You end up with a traceback with KeyError

However, if you reverse it, like this:

>>> b = a[::-1]

Then try the same index, you get the proper result:

>>> b['2008-01-01']
            PETR4  CSNA3  VALE5
Date                           
2008-01-01      0      0      0

I do NOT know why this is the case. Chances are, it has something to do with being a time series one way, but not the other? Someone more knowledgeable should answer that.

Update: By RTFM, I discovered this page:

If you find the section titled “Slice vs. Exact Match”, there is a warning that explains this behavior. The problem seems to be that for a TimeSeries, an exact match is interpreted as a column name. For unsorted dataframes, this doesn’t happen. See the warning box in the section referenced above. I still find this terribly confusing, but there you go…

Conclusion

It’s all About this issue. Hope all Methods helped you a lot. Comment below Your thoughts and your queries. Also, Comment below which Method worked for you? Thank You.

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