文字列検索でも抽出できるとは思うのですが、日時データは datetime型で扱うべきかと思います。
とりあえず、'create_by'列を
df['create_at'] = pd.to_datetime(df['create_at'])
にて'datetime'型に変換した後に、月と日で
df[(df['create_at'].dt.month == 7) & (df['create_at'].dt.day == 1)]
または年も含めて
df[df['create_at'].dt.date == dt.date(2018,7,1)]
のようにするのが良いと思います。
以下動作サンプル
Python
1import io
2import pandas as pd
3import datetime as dt
4
5data = """
6create_at,favorite_count
7Wed Jul 01 08:42:39 +0000 2018,0.0
8Wed Jul 01 08:41:22 +0000 2018,0.0
9Wed Jul 02 08:41:04 +0000 2018,0.0
10Wed Jul 02 08:40:56 +0000 2018,0.0
11Wed Jul 03 08:40:06 +0000 2018,0.0
12Wed Jul 03 08:39:53 +0000 2018,0.0
13Wed Jul 03 08:39:40 +0000 2018,0.0
14Wed Jul 04 08:39:02 +0000 2018,0.0
15Wed Jul 04 08:38:30 +0000 2018,0.0
16Wed Jul 04 08:38:15 +0000 2018,0.0
17"""
18
19df = pd.read_csv(io.StringIO(data))
20df['create_at'] = pd.to_datetime(df['create_at'])
21
22print(df[(df['create_at'].dt.month == 7) & (df['create_at'].dt.day == 1)])
23# create_at favorite_count
24#0 2018-07-01 08:42:39 0.0
25#1 2018-07-01 08:41:22 0.0
26
27print(df[df['create_at'].dt.date == dt.date(2018,7,1)])
28# create_at favorite_count
29#0 2018-07-01 08:42:39 0.0
30#1 2018-07-01 08:41:22 0.0
バッドをするには、ログインかつ
こちらの条件を満たす必要があります。