Pandas - general functions

https://pandas.pydata.org/docs/reference/general_functions.html

CONCAT

https://pandas.pydata.org/docs/reference/api/pandas.concat.html

# pandas.concat(objs, *, axis=0, join='outer', ignore_index=False, keys=None,
#     levels=None, names=None, verify_integrity=False, sort=False, copy=None)
#
# Concatenate pandas objects along a particular axis.

# Combine two Series.
s1 = pd.Series(['a', 'b'])
s2 = pd.Series(['c', 'd'])
s3 = pd.concat([s1, s2], ignore_index=True)   # pd.Series(['a', 'b', 'c', 'd'])
# 0    a
# 1    b
# 2    c
# 3    d
# dtype: object

# Combine two DataFrame objects with identical columns.
df1 = pd.DataFrame([['a', 1], ['b', 2]], columns=['letter', 'number'])
df2 = pd.DataFrame([['c', 3], ['d', 4]], columns=['letter', 'number'])
df3 = pd.concat([df1, df2], ignore_index=True)
#   letter  number
# 0      a       1
# 1      b       2
# 2      c       3
# 3      d       4

# Combine DataFrame objects horizontally along the x axis by passing in axis=1.
df4 = pd.DataFrame([['bird', 'polly'], ['monkey', 'george']],
    columns=['animal', 'name'])
df5 = pd.concat([df1, df4], axis=1)
  letter  number  animal    name
0      a       1    bird   polly
1      b       2  monkey  george

MERGE

https://pandas.pydata.org/docs/reference/api/pandas.merge.html

# pandas.merge(left, right, how='inner', on=None, left_on=None, right_on=None,
#     left_index=False, right_index=False, sort=False, suffixes=('_x', '_y'),
#     copy=None, indicator=False, validate=None)
#
# Merge DataFrame or named Series objects with a database-style join.