Try this instead,

  print(
"{:.3f}% {} ({} sentences)".format(pcent, gender, nsents)
)

Refer the latest docs for more examples and check the Py version!

It's a just syntax error:

Put a colon (:) behind r instead of a point(.) and it will work.

You no longer are in the Pandas API after the round function.

You have to cast the value like so

c_med = int(round(df['count'].median()) 

I'm not too familiar with Pandas, but you could try

c_med = df['count'].median().round().astype(int)

The error points to this line:

df['content'] = df['content'].apply(lambda x: " ".join(x.lower() for x in x.split() \
                                    if x not in stop_words))

split is being used here as a method of Python's built-in str class. Your error indicates one or more values in df['content'] is of type float. This could be because there is a null value, i.e. NaN, or a non-null float value.

One workaround, which will stringify floats, is to just apply str on x before using split:

df['content'] = df['content'].apply(lambda x: " ".join(x.lower() for x in str(x).split() \
                                    if x not in stop_words))

Alternatively, and possibly a better solution, be explicit and use a named function with a try / except clause:

def converter(x):
    try:
        return ' '.join([x.lower() for x in str(x).split() if x not in stop_words])
    except AttributeError:
        return None  # or some other value

df['content'] = df['content'].apply(converter)

Since pd.Series.apply is just a loop with overhead, you may find a list comprehension or map more efficient:

df['content'] = [converter(x) for x in df['content']]
df['content'] = list(map(converter, df['content']))

You need to number the format codes. Also, if you really want to print { when using the new format code, you have to use a double {{ to escape the format:

"M{0:2.2f}, {1:3.2f} km, lat {2:3.3f}N{{DEGREE SIGN}} lon {3:3.3f}\N{{DEGREE SIGN}}".format(
self.mag, self.depth, self.lat, self.lon)