Python Pandas to_datetime
# Introduction to Pandas to_datetime()
The Pandas `to_datetime()` function is a powerful tool for converting a variety of timestamp formats into datetime objects in Python. It is especially useful for dealing with dates and times in data sets that are not in the same format, such as data from different sources or data from different regions. It is also helpful for converting string objects into datetime objects to use in data analysis, such as for time series analysis. This article will cover how to use the `to_datetime()` function and the various parameters that can be passed to it to customize the conversion process.
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**Python Pandas to_datetime**
The `to_datetime` method in the Python Pandas library is used to convert an argument to a datetime object. This can be used to convert strings, timestamps, or other types of data into a datetime object.
**Example**
The following example shows how to use `to_datetime` to convert a string to a datetime object.
```python
import pandas as pd
# Create the string to convert
string_date = "2020-07-29"
# Convert the string to a datetime object
dt_date = pd.to_datetime(string_date)
# Print the datetime object
print(dt_date)
```
Output:
`2020-07-29 00:00:00`
