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I have two dataframes
current_bin.info()
<class 'pandas.core.frame.DataFrame'>
Int64Index: 16 entries, 0 to 15
Data columns (total 3 columns):
id 16 non-null object
fpd 16 non-null float64
avgSpeedBinID 16 non-null object
dtypes: float64(1), object(2)
the current_bin data frame looks like:
current_bin
id fpd avgSpeedBinID
0 1.1.4.1 2.818623 1
1 1.1.4.10 0.266681 10
2 1.1.4.11 0.250017 11
3 1.1.4.12 0.234749 12
4 1.1.4.13 0.222515 13
5 1.1.4.14 0.216150 14
6 1.1.4.15 0.218368 15
7 1.1.4.16 0.227663 16
8 1.1.4.2 1.475454 2
9 1.1.4.3 0.805842 3
10 1.1.4.4 0.581797 4
11 1.1.4.5 0.450314 5
12 1.1.4.6 0.379107 6
13 1.1.4.7 0.335155 7
14 1.1.4.8 0.305992 8
15 1.1.4.9 0.284210 9
and
avg.info()
<class 'pandas.core.frame.DataFrame'>
Int64Index: 16 entries, 0 to 15
Data columns (total 4 columns):
avgSpeedBinID 16 non-null int64
avgBinSpeed 16 non-null float64
avgSpeedBinDesc 16 non-null object
temp 16 non-null int64
dtypes: float64(1), int64(2), object(1)
which looks like:
avgSpeedBinID avgBinSpeed avgSpeedBinDesc temp
0 1 3 speed < 2.5mph 0
1 2 5 2.5mph <= speed < 7.5mph 0
2 3 10 7.5mph <= speed < 12.5mph 0
3 4 15 12.5mph <= speed < 17.5mph 0
4 5 20 17.5mph <= speed <22.5mph 0
5 6 25 22.5mph <= speed < 27.5mph 0
6 7 30 27.5mph <= speed < 32.5mph 0
7 8 35 32.5mph <= speed < 37.5mph 0
8 9 40 37.5mph <= speed < 42.5mph 0
9 10 45 42.5mph <= speed < 47.5mph 0
10 11 50 47.5mph <= speed < 52.5mph 0
11 12 55 52.5mph <= speed < 57.5mph 0
12 13 60 57.5mph <= speed < 62.5mph 0
13 14 65 62.5mph <= speed < 67.5mph 0
14 15 70 67.5mph <= speed < 72.5mph 0
15 16 75 72.5mph <= speed 0
both dataframes have a value 1 to 16 on the avgSpeedBinID field, however, when i try to merge the data frames together
avg.merge(current_bin, on='avgSpeedBinID')
I'm getting a null dataframe
avgSpeedBinID avgBinSpeed avgSpeedBinDesc temp id fpd
Why is this happening and how can i correct the problem?
795
This function takes all the columns of both the datasets to merge i.e. the rows of merge dataframe consists of all rows where the “NOC”, “Country” and “Total” columns are identical in both the dataframes Bronze and Silver Medals. Thus this merge gives us an empty dataframe because the columns values doesn't matches.
Use DataFrame.empty attribute empty attribute to check if the given dataframe is empty or not.
Append Rows to Empty DataFrameDataFrame. append() function is used to add the rows of other DataFrame to the end of the given DataFrame and return a new DataFrame object. Yields below output.
The avgSpeedBinID in the current bin dataframe is type str and in avg is int.
Just cast the str one into an int and the merge will work.
current_bin['avgSpeedBinID'] = current_bin['avgSpeedBinID'].astype(int)
avg.merge(current_bin, on='avgSpeedBinID')
avgSpeedBinID avgBinSpeed avgSpeedBinDesc temp id fpd
0 1 3 speed < 2.5mph 0 1.1.4.1 2.818623
1 2 5 2.5mph <= speed < 7.5mph 0 1.1.4.2 1.475454
2 3 10 7.5mph <= speed < 12.5mph 0 1.1.4.3 0.805842
3 4 15 12.5mph <= speed < 17.5mph 0 1.1.4.4 0.581797
4 5 20 17.5mph <= speed <22.5mph 0 1.1.4.5 0.450314
5 6 25 22.5mph <= speed < 27.5mph 0 1.1.4.6 0.379107
6 7 30 27.5mph <= speed < 32.5mph 0 1.1.4.7 0.335155
7 8 35 32.5mph <= speed < 37.5mph 0 1.1.4.8 0.305992
8 9 40 37.5mph <= speed < 42.5mph 0 1.1.4.9 0.284210
9 10 45 42.5mph <= speed < 47.5mph 0 1.1.4.10 0.266681
10 11 50 47.5mph <= speed < 52.5mph 0 1.1.4.11 0.250017
11 12 55 52.5mph <= speed < 57.5mph 0 1.1.4.12 0.234749
12 13 60 57.5mph <= speed < 62.5mph 0 1.1.4.13 0.222515
13 14 65 62.5mph <= speed < 67.5mph 0 1.1.4.14 0.216150
14 15 70 67.5mph <= speed < 72.5mph 0 1.1.4.15 0.218368
15 16 75 72.5mph <= speed 0 1.1.4.16 0.22763
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