Search for an exact match of a string in pandas.DataFrame

Question

I have a DataFrame as follows:

data = [
    ['2022-12-04 00:00:00', 5000.00],
    ['2022-12-04 00:00:00', 6799.50],
    ['2022-12-04 00:00:00', 5000.00],
    ['2023-01-10 00:00:00', 5000.00]
]

df = pd.DataFrame(data, columns=['Date', 'Float'])


date_input = "2022-12-04 00:00:00"
float_input = "5000.00"

What would be the best way to check if there is a string in DF with an exact match of the values ‘date’ and ‘float’.

In such case, I expect the ‘Yes’ output, since such combination of ‘date’ and ‘float’ is contained in the first line of DataFrame.

I tried it like this, but it doesn’t help to determine if there is a match of ‘float_input’ values for a certain ‘date_input’ date

if ((df['Date'] == pd.Timestamp(date_input)).any()) and (df['Float'] == float(float_input).any():
print('YES')
else:
print("No")

Asked By: Djoe

||

Source

Answer 1

If I am understanding your problem correctly, I believe you can check if there is a string in DF with an exact match of the values ‘date’ and ‘float’ by using the loc method of the DataFrame to select the rows that match the ‘date_input’ and ‘float_input’ values.

Then, you can check if the resulting DataFrame is empty or not, which indicates that there is at least one row with the exact match of ‘date_input’ and ‘float_input’ values.

Modified Code

date_input = "2022-12-04 00:00:00"
float_input = "5000.00"

# Use loc to select the rows that match the values
matches = df.loc[(df['Date'] == pd.Timestamp(date_input)) & (df['Float'] == float(float_input))]

# Check if the resulting DataFrame is empty or not
if not matches.empty:
    print('YES')
else:
    print('NO')

Answered By: CRM000

Answer 2

if [date_input,float_input] in df.values:

print(‘yes’)

else:

print(‘no’)

Answered By: ilshatt

Answer 3

Good night friend, I performed the process you tried. First, let’s break it down:

Step 1:

Your data set has incorrect values, you have to correct the date to a string before placing it in pd.DataFrame.

data = [
['2022-12-04 00:00:00', 5000.00],
['2022-12-04 00:00:00', 6799.50],
['2022-12-04 00:00:00', 5000.00],
['2023-01-10 00:00:00', 5000.00]]

Step 2:

After solving the previous question, we perform the dateframe process:

Now we can visualize the dateframe, right after that we see that the column that one of the columns we are looking for has a type problem, so we must carry out the conversion

Step 3:

Using one of the pandas tools, we can convert the type to datetime, you can see that I used the dayfirst parameter, this is optional, but since we don’t have hours, minutes and seconds. I didn’t choose telos. I followed the documentation which you will find quite interesting.

df['Date'] = pd.to_datetime(df['Date'], dayfirst=True)

Step 4:

Let’s go to the consultations, in a simple way, performing a consultation by parts, looking for one at a time. We found your values query

SearchDate =  df[df['Date'] == pd.Timestamp("2022-12-04 00:00:00'")]
SearchNumber =  SearchDate[SearchDate['Float'] == 5000.00]
SearchNumber

Another way to search is for the indexes that return True from each query, using the and operator, we manage to return the values of the query

searchDate =  df['Date'] == pd.Timestamp("2022-12-04 00:00:00'") 
seachFloat = df['Float'] == 5000.00
query = df[searchDate & seachFloat]
query

Carrying out the table in the previous step in another form of execution

query_dataframe = df[(df['Date'] == pd.Timestamp("2022-12-04 00:00:00")) & (df['Float'] == 5000.00)]
query_dataframe

step 5:

This check you put I didn’t understand very well. In a simple way, I checked if the variable is empty, I performed the return as in your example

if len(query_dataframe):
    print('Yes')
else:
    print('No')

Answered By: Eddi

Search for an exact match of a string in pandas.DataFrame

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