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Writing a pandas DataFrame to CSV file

I have a dataframe in pandas which I would like to write to a CSV file.

I am doing this using:

df.to_csv('out.csv')

And getting the following error:

UnicodeEncodeError: 'ascii' codec can't encode character u'\u03b1' in position 20: ordinal not in range(128)

Is there any way to get around this easily (i.e. I have unicode characters in my data frame)?
And is there a way to write to a tab delimited file instead of a CSV using e.g. a 'to-tab' method (that I don't think exists)?

Answer*

#### 1. `errors=` is sometimes useful

If a file has to have a certain encoding but the existing dataframe has characters that cannot be represented, `errors=` can be used to "coerce" the data to be saved anyway at the _cost of losing information_. All possible values that can be passed as the `errors=` argument to the [`open()` function in Python][1] can be passed here.

For example, the below code saves a csv with ascii encoding where the Japanese characters are replaced with a `?`.
```python
df = pd.DataFrame({'A': ['Shohei Ohtani は一生に一度の選手だ。']})
df.to_csv('data1.csv', encoding='ascii', errors='replace', index=False)

print(pd.read_csv('data1.csv'))

A
0  Shohei Ohtani ???????????
```

#### 2. `float_format=` is sometimes useful

You can format float dtypes using `float_format=` and doing so saves a lot of memory sometimes at _the cost of losing precision_. For example, 
```python
df = pd.DataFrame({'A': [*range(1,9,3)]*1000})/3
df.to_csv('data1.csv', index=False)                       # 61,440 bytes on disk
df.to_csv('data2.csv', index=False, float_format='%.2f')  # 20,480 bytes on disk
```

#### 3. Save a compressed csv

Since pandas 1.0.0, you can pass a dict to compression that specifies compression method and file name inside the archive. The below code creates a zip file named `compressed_data.zip` which has a single file in it named `data.csv`.
```python
df.to_csv('compressed_data.zip', index=False, compression={'method': 'zip', 'archive_name': 'data.csv'})
# read the archived file as a csv
pd.read_csv('compressed_data.zip')
```
You can even add to an existing archive; simply pass `mode='a'`.
```python
df.to_csv('compressed_data.zip', compression={'method': 'zip', 'archive_name': 'data_new.csv'}, mode='a')
```

[1]: https://docs.python.org/3/library/functions.html#open

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Writing a pandas DataFrame to CSV file

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