Conversion

Public conversion helpers

• to_jalali_datetime(...)
• to_gregorian_datetime(...)

import pandas as pd
import jalali_pandas as jp

jp.to_jalali_datetime("1402-06-15")

jp.to_jalali_datetime(pd.Timestamp("2023-09-06"))

jp.to_jalali_datetime(["1402-01-01", "1402-01-02"])

jidx = jp.JalaliDatetimeIndex(["1402-01-01", "1402-01-02"])
jp.to_gregorian_datetime(jidx)

Error handling

to_jalali_datetime(..., errors=...) supports:

• "raise" (default)
• "coerce" → invalid values become pd.NaT
• "ignore" → return the original input (only for Series)

Supported string formats (when format=None)

The parser tries these formats in order:

• %Y-%m-%d %H:%M:%S
• %Y-%m-%d
• %Y/%m/%d %H:%M:%S
• %Y/%m/%d
• %Y%m%d

Vectorized conversion helpers

These are internal helpers used by arrays and indexes:

• gregorian_to_jalali_vectorized
• jalali_to_gregorian_vectorized
• datetime64_to_jalali
• jalali_to_datetime64

Use the public API unless you need lower-level access.