Left merging a 6628 row DF with a 127286 row DF yields a 48939191 row DF
#### Code Sample, a copy-pastable example if possible

```python
[ins] In [10]: df_e2.info()                                                                                                                                                          
<class 'pandas.core.frame.DataFrame'>
Int64Index: 127286 entries, 0 to 6327
Data columns (total 24 columns):
 #   Column          Non-Null Count   Dtype         
---  ------          --------------   -----         
 0   revenue         18258 non-null   string        
 1   phone           49570 non-null   string        
 2   status          127286 non-null  string        
 3   notes           66101 non-null   string        
 4   facebook_url    43003 non-null   string        
 5   linkedin_url    52043 non-null   string        
 6   email           50212 non-null   string        
 7   description     119431 non-null  string        
 8   crunchbase_url  76787 non-null   string        
 9   name            127286 non-null  string        
 10  url             113731 non-null  string        
 11  twitter_handle  56307 non-null   string        
 12  hq_location     72719 non-null   string        
 13  latitude        72719 non-null   float64       
 14  longitude       72719 non-null   float64       
 15  country_code    72697 non-null   string        
 16  url_redir       47957 non-null   string        
 17  founding_year   127286 non-null  string        
 18  created_at      127286 non-null  datetime64[ns]
 19  updated_at      127286 non-null  datetime64[ns]
 20  type            127286 non-null  string        
 21  raw_tags        127286 non-null  object        
 22  database_id     127286 non-null  Int64         
 23  dupe_group_ix   127286 non-null  Int64         
dtypes: Int64(2), datetime64[ns](2), float64(2), object(1), string(17)
memory usage: 24.5+ MB

[ins] In [11]: df.info()                                                                                                                                                             
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 6629 entries, 0 to 6628
Data columns (total 37 columns):
 #   Column                         Non-Null Count  Dtype         
---  ------                         --------------  -----         
 0   id                             6629 non-null   Int64         
 1   name                           6629 non-null   string        
 2   url                            6370 non-null   string        
 3   description                    6593 non-null   string        
 4   created_at                     6629 non-null   datetime64[ns]
 5   updated_at                     6629 non-null   datetime64[ns]
 6   email                          6481 non-null   string        
 7   slug                           6021 non-null   string        
 8   raw_tags                       6629 non-null   object        
 9   short_description              157 non-null    string        
 10  twitter_handle                 5069 non-null   string        
 11  hq_location                    6428 non-null   string        
 12  latitude                       6416 non-null   float64       
 13  longitude                      6416 non-null   float64       
 14  company_registration_number    61 non-null     string        
 15  company_registrar_url          163 non-null    string        
 16  tax_registration_number        52 non-null     string        
 17  tax_registrar_url              51 non-null     string        
 18  financial_registration_number  56 non-null     string        
 19  financial_registrar_url        56 non-null     string        
 20  instagram_handle               80 non-null     string        
 21  crunchbase_url                 5660 non-null   string        
 22  facebook_url                   4319 non-null   string        
 23  linkedin_url                   5097 non-null   string        
 24  bloomberg_url                  81 non-null     string        
 25  founding_year                  5842 non-null   Int64         
 26  revenue                        2020 non-null   string        
 27  type                           6472 non-null   string        
 28  blog_url                       113 non-null    string        
 29  rss_url                        51 non-null     string        
 30  country_code                   6397 non-null   string        
 31  domain_name                    203 non-null    string        
 32  phone                          4009 non-null   string        
 33  database_id                    6629 non-null   Int64         
 34  status                         6629 non-null   string        
 35  notes                          6458 non-null   string        
 36  complete                       214 non-null    boolean       
dtypes: Int64(3), boolean(1), datetime64[ns](2), float64(2), object(1), string(28)
memory usage: 1.9+ MB

[nav] In [13]: df2 = df.merge(df_e2, on='crunchbase_url', how='left', copy=False)                                                                                                    

[ins] In [14]: df2.info()                                                                                                                                                            
<class 'pandas.core.frame.DataFrame'>
Int64Index: 48939191 entries, 0 to 48939190
Data columns (total 60 columns):
 #   Column                         Dtype         
---  ------                         -----         
 0   id                             Int64         
 1   name_x                         string        
 2   url_x                          string        
 3   description_x                  string        
 4   created_at_x                   datetime64[ns]
 5   updated_at_x                   datetime64[ns]
 6   email_x                        string        
 7   slug                           string        
 8   raw_tags_x                     object        
 9   short_description              string        
 10  twitter_handle_x               string        
 11  hq_location_x                  string        
 12  latitude_x                     float64       
 13  longitude_x                    float64       
 14  company_registration_number    string        
 15  company_registrar_url          string        
 16  tax_registration_number        string        
 17  tax_registrar_url              string        
 18  financial_registration_number  string        
 19  financial_registrar_url        string        
 20  instagram_handle               string        
 21  crunchbase_url                 string        
 22  facebook_url_x                 string        
 23  linkedin_url_x                 string        
 24  bloomberg_url                  string        
 25  founding_year_x                Int64         
 26  revenue_x                      string        
 27  type_x                         string        
 28  blog_url                       string        
 29  rss_url                        string        
 30  country_code_x                 string        
 31  domain_name                    string        
 32  phone_x                        string        
 33  database_id_x                  Int64         
 34  status_x                       string        
 35  notes_x                        string        
 36  complete                       boolean       
 37  revenue_y                      string        
 38  phone_y                        string        
 39  status_y                       string        
 40  notes_y                        string        
 41  facebook_url_y                 string        
 42  linkedin_url_y                 string        
 43  email_y                        string        
 44  description_y                  string        
 45  name_y                         string        
 46  url_y                          string        
 47  twitter_handle_y               string        
 48  hq_location_y                  string        
 49  latitude_y                     float64       
 50  longitude_y                    float64       
 51  country_code_y                 string        
 52  url_redir                      string        
 53  founding_year_y                string        
 54  created_at_y                   datetime64[ns]
 55  updated_at_y                   datetime64[ns]
 56  type_y                         string        
 57  raw_tags_y                     object        
 58  database_id_y                  Int64         
 59  dupe_group_ix                  Int64         
dtypes: Int64(5), boolean(1), datetime64[ns](4), float64(4), object(2), string(44)
memory usage: 22.2+ GB

[ins] In [15]: pd.__version__                                                                                                                                                        
Out[15]: '1.0.1'

[ins] In [16]: len(df)                                                                                                                                                               
Out[16]: 6629

[ins] In [17]: len(df_e2)                                                                                                                                                            
Out[17]: 127286

[ins] In [18]: len(df2)                                                                                                                                                              
Out[18]: 48939191


```

<details>

[paste the output of ``pd.show_versions()`` here below this line]
INSTALLED VERSIONS
------------------
commit           : None
python           : 3.7.3.final.0
python-bits      : 64
OS               : Linux
OS-release       : 4.4.0-1101-aws
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.0.1
numpy            : 1.16.4
pytz             : 2019.3
dateutil         : 2.8.0
pip              : 19.1.1
setuptools       : 41.0.1
Cython           : 0.29.12
pytest           : 5.0.1
hypothesis       : None
sphinx           : 2.1.2
blosc            : None
feather          : None
xlsxwriter       : 1.1.8
lxml.etree       : 4.3.4
html5lib         : 1.0.1
pymysql          : None
psycopg2         : 2.8.4 (dt dec pq3 ext lo64)
jinja2           : 2.10.1
IPython          : 7.6.1
pandas_datareader: None
bs4              : 4.7.1
bottleneck       : 1.2.1
fastparquet      : None
gcsfs            : None
lxml.etree       : 4.3.4
matplotlib       : 3.1.0
numexpr          : 2.6.9
odfpy            : None
openpyxl         : 2.6.2
pandas_gbq       : None
pyarrow          : 0.12.1
pytables         : None
pytest           : 5.0.1
pyxlsb           : None
s3fs             : None
scipy            : 1.3.0
sqlalchemy       : 1.3.5
tables           : 3.5.2
tabulate         : 0.8.5
xarray           : None
xlrd             : 1.2.0
xlwt             : 1.3.0
xlsxwriter       : 1.1.8
numba            : 0.44.1

</details>
