10 tricks for converting numbers and strings to datetime in pandas Time series / date functionality # pandas contains extensive capabilities and features for working with time series data for all domains. In another post I learned of a technique that speeds this up dramatically when the number of unique values is much smaller than the number of rows. to_datetime() function, which can automatically parse various date formats. Apr 14, 2021 · The simplest way to convert a Pandas column to a different type is to use the Series’ method astype(). Nov 4, 2025 · Explore effective methods to convert string columns to datetime objects in Pandas. timeseries as well as created a tremendous amount of new functionality for manipulating time series data. ) It first builds a dict that maps the text dates to their datetime objects, then applies the dict to convert the column of Jun 2, 2025 · Conclusion Datetime conversion in Pandas is a critical step in unlocking the full potential of time series analysis. to_datetime() The most common first step in working with date and time data in Pandas is converting your raw data (often strings or numbers) into proper datetime objects. . Timestamp. (My data is usually stock price or trade blotter data. Pandas To Datetime (. datetime64[ns, UTC]) objects. to_datetime(df['Date Oct 20, 2014 · I find letting pandas do the work to be too slow on large dataframes. to_datetime () function method to convert string columns to datetime format. Sep 2, 2025 · Converting Data to Datetime with pd. Using pd. to_datetime () pd. Apr 20, 2021 · This article will discuss how to convert numbers and strings to a datetime type. However, a common frustration arises when Pandas automatically parses columns containing dates (or date-like strings) into `datetime` objects—even when you want to preserve the original string format. to_datetime()) will convert your string representation of a date to an actual date format. The process of converting these raw strings into a dedicated datetime data type—specifically the highly optimized datetime64[ns] format utilized by Pandas—transforms them into structured, numerical objects that the library can interpret and manipulate with maximum efficiency. By mastering pd. 1 Converting Strings to Datetime Pandas provides the pd. Nov 1, 2025 · In this article, we will explore different methods to convert a column containing date strings into proper datetime format in a Pandas DataFrame. In pandas we call these datetime objects similar to datetime. For example: import pandas as pd data = {'Date': ['2023-01-01', '2023-02-15', '2023-07-04', '2023-12-25']} df = pd. It automatically handles many date formats. ,I'm trying to convert these to datetime: Example, with unit='ms' and origin='unix', this would calculate the number of milliseconds to the unix epoch start. Parsing Dates in pandas When working with datasets that contain date information, it’s essential to correctly parse and convert these strings into pandas datetime objects. to_datetime method to convert a column of strings to a column of datetime objects. This can lead to issues like lost formatting (e. This is achieved using the pd. Converting to Datetime The first step is often to convert strings or other data formats into Pandas’ datetime format. For Interested in my Top 10 Pandas Functions? Get em here. Key Features 1. For instance, to convert strings to integers we can call it like: Nov 15, 2022 · I have a series with some datetimes (as strings) and some nulls as 'nan':,How to convert string to datetime with nulls - python, pandas? ,but it will be faster to use the inbuilt to_datetime rather than call apply which essentially just loops over your series. , "05/10/2023" vs. DataFrame(data) df['Date'] = pd. More specifically, you will learn how to use the Pandas built-in methods to_datetime() and astype() to deal with Jun 16, 2013 · 79 If your date column is a string of the format '2017-01-01' you can use pandas astype to convert it to datetime. Jun 20, 2019 · By applying the to_datetime function, pandas interprets the strings and convert these to datetime (i. Using the NumPy datetime64 and timedelta64 dtypes, pandas has consolidated a large number of features from other Python libraries like scikits. e. infer_datetime_formatbool, default False If True and no format is given, attempt to infer the format of the datetime strings based on the first non-NaN element, and if it can be inferred, switch to a faster method of parsing them. Learn about to_datetime, astype, format specifiers, infer_datetime_format, and performance tips for large datasets. For Aug 9, 2016 · 4 You can add parameter dtype to read_csv for converting column col to string and then use to_datetime with parameters format for specify formatting and errors='coerce' - because bad dates, which are converted to NaT: 5 days ago · When working with Excel files in Python, Pandas’ `read_excel` function is a go-to tool for data ingestion. g. Converts various data types (strings, integers, floats, lists, dictionaries) into pandas' specialized datetime objects (Timestamp or DatetimeIndex). "2023-10-05 May 27, 2025 · Enables pandas to handle dates and times effectively for tasks like time series analysis, date calculations, and data filtering based on time criteria. to_datetime function. Jan 13, 2023 · Here are some common tasks you might want to do with datetime data in Pandas: Create a datetime column in a Pandas DataFrame - we can use the pd. Jan 15, 2025 · Let’s learn on how to handle datetime data in Pandas. datetime from the standard library as pandas. 1. to_datetime () and related methods, you can standardize date formats, handle timezones, and extract meaningful components for analysis. This is extremely important when utilizing all of the Pandas Date functionality like resample. qgiaup tfsyj lweu wxfoi imzffhr zsjs ujpr wjedk lod ykkcez ugtj thrzlq jtpo kdnsssf vlb