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import streamlit as st
import pandas as pd
from io import BytesIO
# Define the button and title styles
styles = """
<style>
/* Button styles */
div.stButton > button {
color: #ffffff; /* Text color */
font-size: 20px;
background-image: linear-gradient(0deg, #a2c2e1 0%, #003b5c 100%); /* Light blue to deep blue gradient */
border: none;
padding: 10px 20px;
cursor: pointer;
border-radius: 15px;
display: inline-block;
width: 100%; /* Make button fit column width */
}
div.stButton > button:hover {
background-color: #00ff00; /* Hover background color */
color: #ff0000; /* Hover text color */
}
/* Title styles */
h1 {
background-image: linear-gradient(0deg, #a2c2e1 0%, #003b5c 100%); /* Light blue to deep blue gradient */
-webkit-background-clip: text;
-webkit-text-fill-color: transparent;
font-size: 36px;
}
</style>
"""
# Set up the Streamlit app
st.markdown(styles, unsafe_allow_html=True)
# Custom gradient title
st.markdown("<h1>CSV and Excel Appender</h1>", unsafe_allow_html=True)
st.write("A website that is used for appending multiple CSV and Excel files and converting them to a desired format.")
# File uploader for multiple CSV and Excel files
uploaded_files = st.file_uploader("Upload CSV or Excel files", type=["csv", "xlsx", "xls"], accept_multiple_files=True)
if uploaded_files:
# Initialize an empty list to store DataFrames
df_list = []
for i, uploaded_file in enumerate(uploaded_files):
# Get the file name without extension
file_name = uploaded_file.name
# Check the file type and read accordingly
if uploaded_file.type == "text/csv":
if i == 0:
# For the first file, include the header
df = pd.read_csv(uploaded_file)
# Store the columns from the first file
headers = df.columns
else:
# For subsequent files, set the header using the stored headers
df = pd.read_csv(uploaded_file, names=headers, header=0)
elif uploaded_file.type == "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet":
if i == 0:
# For the first file, include the header
df = pd.read_excel(uploaded_file)
# Store the columns from the first file
headers = df.columns
else:
# For subsequent files, set the header using the stored headers
df = pd.read_excel(uploaded_file, names=headers, header=0)
elif uploaded_file.type == "application/vnd.ms-excel":
# This is an .xls file
if i == 0:
# For the first file, include the header
df = pd.read_excel(uploaded_file, engine='xlrd')
# Store the columns from the first file
headers = df.columns
else:
# For subsequent files, set the header using the stored headers
df = pd.read_excel(uploaded_file, names=headers, header=0, engine='xlrd')
# Add a column for the file name
df['file_name'] = file_name
df_list.append(df)
# Concatenate all DataFrames, ignoring index to avoid duplication
merged_df = pd.concat(df_list, ignore_index=True)
# Display the merged DataFrame
st.markdown("<h1>Appended Data</h1>", unsafe_allow_html=True)
st.dataframe(merged_df)
# Create a layout with 3 columns for buttons
col1, col2, col3 = st.columns(3)
with col1:
# Provide a download button for the merged CSV file
csv_output = BytesIO()
merged_df.to_csv(csv_output, index=False)
csv_output.seek(0)
st.download_button(
label="Download Merged CSV File",
data=csv_output,
file_name="merged_data.csv",
mime="text/csv"
)
with col2:
# Provide an option to convert to Excel
excel_output = BytesIO()
with pd.ExcelWriter(excel_output, engine='xlsxwriter') as writer:
merged_df.to_excel(writer, index=False)
excel_output.seek(0)
st.download_button(
label="Download Merged Excel File",
data=excel_output,
file_name="merged_data.xlsx",
mime="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
)
else:
st.write("") |