My csv file has a column with date times in it that look like this :
"2021-01-24 20:10:58"
and I've written the following :
import pandas as pd
data = pd.read_csv(r'C:\Users\user\Desktop\foo\data.csv', index_col=1, parse_dates=True, infer_datetime_format=True)
print(data.dtypes)
which shows basically all of my columns as 'object' type. Can someone help me understand what I'm missing?
You should pass a list of column names or indices, e.g. parse_dates=["col1", "col2"] or parse_dates=[1, 2]. If you pass parse_dates=True, only the index column will be parsed.
Per the docs:
The behavior is as follows:
boolean. If True -> try parsing the index.
list of int or names. e.g. If [1, 2, 3] -> try parsing columns 1, 2, 3 each as a separate date column.
list of lists. e.g. If [[1, 3]] -> combine columns 1 and 3 and parse as a single date column.
dict, e.g. {‘foo’ : [1, 3]} -> parse columns 1, 3 as date and call result ‘foo’
df.dtypes. Indices are treated differently than columns. You can access the dtype of the index with df.index.dtype.